Distributed lidar systems and methods thereof

ABSTRACT

A LIDAR system, comprising: (a) a plurality of anchored LIDAR sensing units, each anchored LIDAR sensing unit comprising at least: (i) a housing; (ii) at least one detector, mounted in the housing, configured to detect light signals arriving from objects in a field of view of the anchored LIDAR sensing unit; and (iii) a communication unit, configured to output detection information which is based on outputs of the at least one detector and which is indicative of existence of the objects; and (b) at least one integratory processing unit, configured to receive the detection information from two or more of the plurality of anchored LIDAR sensing units, and to process the received detection information to provide a three dimensional model of a scene which is larger than any of the field of views of the independent anchored LIDAR sensing units.

BACKGROUND

This application is a continuation of U.S. application Ser. No.16/255,329, filed Jan. 23, 2019, which claims priority from U.S.Provisional Patent Application No. 62/620,785, filed Jan. 23, 2018. Allof the foregoing applications are incorporated herein by reference intheir entirety.

RELATED APPLICATION Technical Field

The present disclosure relates generally to surveying technology forscanning a surrounding environment, and, more specifically, to systemsand methods that use LIDAR technology to detect objects in thesurrounding environment.

Background Information

With the advent of driver assist systems and autonomous vehicles,automobiles need to be equipped with systems capable of reliably sensingand interpreting their surroundings, including identifying obstacles,hazards, objects, and other physical parameters that might impactnavigation of the vehicle. To this end, a number of differingtechnologies have been suggested including radar, LIDAR, camera-basedsystems, operating alone or in a redundant manner.

One consideration with driver assistance systems and autonomous vehiclesis an ability of the system to determine surroundings across differentconditions including, rain, fog, darkness, bright light, and snow. Alight detection and ranging system, (LIDAR a/k/a LADAR) is an example oftechnology that can work well in differing conditions, by measuringdistances to objects by illuminating objects with light and measuringthe reflected pulses with a sensor. A laser is one example of a lightsource that can be used in a LIDAR system. As with any sensing system,in order for a LIDAR-based sensing system to be fully adopted by theautomotive industry, the system should provide reliable data enablingdetection of far-away objects. Currently, however, the maximumillumination power of LIDAR systems is limited by the need to make theLIDAR systems eye-safe (i.e., so that they will not damage the human eyewhich can occur when a projected light emission is absorbed in the eye'scornea and lens, causing thermal damage to the retina.)

The systems and methods of the present disclosure are directed towardsimproving performance of LIDAR systems.

SUMMARY

In an embodiment, a LIDAR system may include: (a) a plurality ofanchored LIDAR sensing units, each anchored LIDAR sensing unitcomprising at least: (i) a housing; (ii) at least one detector, mountedin the housing, configured to detect light signals arriving from objectsin a field of view of the anchored LIDAR sensing unit; and (iii) acommunication unit, configured to output detection information which isbased on outputs of the at least one detector and which is indicative ofexistence of the objects; and (b) at least one integratory processingunit, configured to receive the detection information from two or moreof the plurality of anchored LIDAR sensing units, and to process thereceived detection information to provide a three dimensional (3D) modelof a scene which is larger than any of the fields of view of theindependent anchored LIDAR sensing units.

In an embodiment, a method for LIDAR processing in a distributed LIDARsystem may include: (a) receiving detection information from a pluralityof anchored LIDAR sensing units, each covering a different field ofview; (b) processing the received detection information to provide a 3Dmodel of a scene which is larger than any of the fields of view of theindependent anchored LIDAR sensing units; (c) preparing different 3Ddata to send to different recipients; and (d) sending different 3D dataof the scene to different recipients.

In an embodiment, an integratory LIDAR system may include: (a) acommunication module for receiving detection information from aplurality of anchored LIDAR sensing units; and (b) a processorconfigured to process the detection information received from theplurality of anchored LIDAR sensing unit to provide a 3D model of ascene which is larger than any of the fields of view of the independentanchored LIDAR sensing units.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this disclosure, illustrate various disclosed embodiments. Inthe drawings:

FIG. 1A is a diagram illustrating an exemplary LIDAR system consistentwith disclosed embodiments.

FIG. 1B is an image showing an exemplary output of a single scanningcycle of a LIDAR system mounted on a vehicle consistent with disclosedembodiments.

FIG. 1C is another image showing a representation of a point cloud modeldetermined from output of a LIDAR system consistent with disclosedembodiments.

FIGS. 2A-2G are diagrams illustrating different configurations ofprojecting units in accordance with some embodiments of the presentdisclosure.

FIGS. 3A-3D are diagrams illustrating different configurations ofscanning units in accordance with some embodiments of the presentdisclosure.

FIGS. 4A-4E are diagrams illustrating different configurations ofsensing units in accordance with some embodiments of the presentdisclosure.

FIG. 5A includes four example diagrams illustrating emission patterns ina single frame-time for a single portion of the field of view.

FIG. 5B includes three example diagrams illustrating emission scheme ina single frame-time for the whole field of view.

FIG. 5C is a diagram illustrating the actual light emission projectedtowards a field of view and reflections received during a singleframe-time for the whole field of view.

FIGS. 6A-6C are diagrams illustrating a first example implementationconsistent with some embodiments of the present disclosure.

FIG. 6D is a diagram illustrating a second example implementationconsistent with some embodiments of the present disclosure.

FIGS. 7A through 7E illustrate examples of distributed LIDAR systemsdeployed across different environments, in accordance with examples ofthe presently disclosed subject matter.

FIG. 8 is a flow chart illustrating a method for an integratoryprocessing unit in a distributed LIDAR system, in accordance withexamples of the presently disclosed subject matter.

FIG. 9 is a block diagram of an integratory processing unit, inaccordance with examples of the presently disclosed subject matter.

FIG. 10A illustrates a distributed LIDAR system in which an integratoryprocessing unit modified the detection ranges of otherwise identicalLIDAR sensing units, in accordance with examples of the presentlydisclosed subject matter.

FIG. 10B illustrates the FOV of an anchored LIDAR sensing unit indifferent operational states, in accordance with examples of thepresently disclosed subject matter.

FIGS. 11A and 11B illustrate examples of a sensor-carrying scoutingvehicle, in accordance with examples of the presently disclosed subjectmatter.

DETAILED DESCRIPTION

The following detailed description refers to the accompanying drawings.Wherever possible, the same reference numbers are used in the drawingsand the following description to refer to the same or similar parts.While several illustrative embodiments are described herein,modifications, adaptations and other implementations are possible. Forexample, substitutions, additions or modifications may be made to thecomponents illustrated in the drawings, and the illustrative methodsdescribed herein may be modified by substituting, reordering, removing,or adding steps to the disclosed methods. Accordingly, the followingdetailed description is not limited to the disclosed embodiments andexamples. Instead, the proper scope is defined by the appended claims.

Terms Definitions

Disclosed embodiments may involve an optical system. As used herein, theterm “optical system” broadly includes any system that is used for thegeneration, detection and/or manipulation of light. By way of exampleonly, an optical system may include one or more optical components forgenerating, detecting and/or manipulating light. For example, lightsources, lenses, mirrors, prisms, beam splitters, collimators,polarizing optics, optical modulators, optical switches, opticalamplifiers, optical detectors, optical sensors, fiber optics,semiconductor optic components, while each not necessarily required, mayeach be part of an optical system. In addition to the one or moreoptical components, an optical system may also include other non-opticalcomponents such as electrical components, mechanical components,chemical reaction components, and semiconductor components. Thenon-optical components may cooperate with optical components of theoptical system. For example, the optical system may include at least oneprocessor for analyzing detected light.

Consistent with the present disclosure, the optical system may be aLIDAR system. As used herein, the term “LIDAR system” broadly includesany system which can determine values of parameters indicative of adistance between a pair of tangible objects based on reflected light. Inone embodiment, the LIDAR system may determine a distance between a pairof tangible objects based on reflections of light emitted by the LIDARsystem. As used herein, the term “determine distances” broadly includesgenerating outputs which are indicative of distances between pairs oftangible objects. The determined distance may represent the physicaldimension between a pair of tangible objects. By way of example only,the determined distance may include a line of flight distance betweenthe LIDAR system and another tangible object in a field of view of theLIDAR system. In another embodiment, the LIDAR system may determine therelative velocity between a pair of tangible objects based onreflections of light emitted by the LIDAR system. Examples of outputsindicative of the distance between a pair of tangible objects include: anumber of standard length units between the tangible objects (e.g.number of meters, number of inches, number of kilometers, number ofmillimeters), a number of arbitrary length units (e.g. number of LIDARsystem lengths), a ratio between the distance to another length (e.g. aratio to a length of an object detected in a field of view of the LIDARsystem), an amount of time (e.g. given as standard unit, arbitrary unitsor ratio, for example, the time it takes light to travel between thetangible objects), one or more locations (e.g. specified using an agreedcoordinate system, specified in relation to a known location), and more.

The LIDAR system may determine the distance between a pair of tangibleobjects based on reflected light. In one embodiment, the LIDAR systemmay process detection results of a sensor which creates temporalinformation indicative of a period of time between the emission of alight signal and the time of its detection by the sensor. The period oftime is occasionally referred to as “time of flight” of the lightsignal. In one example, the light signal may be a short pulse, whoserise and/or fall time may be detected in reception. Using knowninformation about the speed of light in the relevant medium (usuallyair), the information regarding the time of flight of the light signalcan be processed to provide the distance the light signal traveledbetween emission and detection. In another embodiment, the LIDAR systemmay determine the distance based on frequency phase-shift (or multiplefrequency phase-shift). Specifically, the LIDAR system may processinformation indicative of one or more modulation phase shifts (e.g. bysolving some simultaneous equations to give a final measure) of thelight signal. For example, the emitted optical signal may be modulatedwith one or more constant frequencies. The at least one phase shift ofthe modulation between the emitted signal and the detected reflectionmay be indicative of the distance the light traveled between emissionand detection. The modulation may be applied to a continuous wave lightsignal, to a quasi-continuous wave light signal, or to another type ofemitted light signal. It is noted that additional information may beused by the LIDAR system for determining the distance, e.g. locationinformation (e.g. relative positions) between the projection location,the detection location of the signal (especially if distanced from oneanother), and more.

In some embodiments, the LIDAR system may be used for detecting aplurality of objects in an environment of the LIDAR system. The term“detecting an object in an environment of the LIDAR system” broadlyincludes generating information which is indicative of an object thatreflected light toward a detector associated with the LIDAR system. Ifmore than one object is detected by the LIDAR system, the generatedinformation pertaining to different objects may be interconnected, forexample a car is driving on a road, a bird is sitting on the tree, a mantouches a bicycle, a van moves towards a building. The dimensions of theenvironment in which the LIDAR system detects objects may vary withrespect to implementation. For example, the LIDAR system may be used fordetecting a plurality of objects in an environment of a vehicle on whichthe LIDAR system is installed, up to a horizontal distance of 100 m (or200 m, 300 m, etc.), and up to a vertical distance of 10 m (or 25 m, 50m, etc.). In another example, the LIDAR system may be used for detectinga plurality of objects in an environment of a vehicle or within apredefined horizontal range (e.g., 25°, 50°, 100°, 180°, etc.), and upto a predefined vertical elevation (e.g., ±10°, ±20°, +40°−20°, ±90° or0°−90°.

As used herein, the term “detecting an object” may broadly refer todetermining an existence of the object (e.g., an object may exist in acertain direction with respect to the LIDAR system and/or to anotherreference location, or an object may exist in a certain spatial volume).Additionally or alternatively, the term “detecting an object” may referto determining a distance between the object and another location (e.g.a location of the LIDAR system, a location on earth, or a location ofanother object). Additionally or alternatively, the term “detecting anobject” may refer to identifying the object (e.g. classifying a type ofobject such as car, plant, tree, road; recognizing a specific object(e.g., the Washington Monument); determining a license plate number;determining a composition of an object (e.g., solid, liquid,transparent, semitransparent); determining a kinematic parameter of anobject (e.g., whether it is moving, its velocity, its movementdirection, expansion of the object). Additionally or alternatively, theterm “detecting an object” may refer to generating a point cloud map inwhich every point of one or more points of the point cloud mapcorrespond to a location in the object or a location on a face thereof.In one embodiment, the data resolution associated with the point cloudmap representation of the field of view may be associated with 0.1°×0.1°or 0.3°×0.3° of the field of view.

Consistent with the present disclosure, the term “object” broadlyincludes a finite composition of matter that may reflect light from atleast a portion thereof. For example, an object may be at leastpartially solid (e.g. cars, trees); at least partially liquid (e.g.puddles on the road, rain); at least partly gaseous (e.g. fumes,clouds); made from a multitude of distinct particles (e.g. sand storm,fog, spray); and may be of one or more scales of magnitude, such as ˜1millimeter (mm), ˜5 mm, ˜10 mm, ˜50 mm, ˜100 mm, ˜500 mm, —1 meter (m),˜5 m, ˜10 m, ˜50 m, ˜100 m, and so on. Smaller or larger objects, aswell as any size in between those examples, may also be detected. It isnoted that for various reasons, the LIDAR system may detect only part ofthe object. For example, in some cases, light may be reflected from onlysome sides of the object (e.g., only the side opposing the LIDAR systemwill be detected); in other cases, light may be projected on only partof the object (e.g. laser beam projected onto a road or a building); inother cases, the object may be partly blocked by another object betweenthe LIDAR system and the detected object; in other cases, the LIDAR'ssensor may only detect light reflected from a portion of the object,e.g., because ambient light or other interferences interfere withdetection of some portions of the object.

Consistent with the present disclosure, a LIDAR system may be configuredto detect objects by scanning the environment of the LIDAR system. Theterm “scanning the environment of the LIDAR system” broadly includesilluminating the field of view or a portion of the field of view of theLIDAR system. In one example, scanning the environment of the LIDARsystem may be achieved by moving or pivoting a light deflector todeflect light in differing directions toward different parts of thefield of view. In another example, scanning the environment of the LIDARsystem may be achieved by changing a positioning (i.e. location and/ororientation) of a sensor with respect to the field of view. In anotherexample, scanning the environment of the LIDAR system may be achieved bychanging a positioning (i.e. location and/or orientation) of a lightsource with respect to the field of view. In yet another example,scanning the environment of the LIDAR system may be achieved by changingthe positions of at least one light source and of at least one sensor tomove rigidly with respect to the field of view (i.e. the relativedistance and orientation of the at least one sensor and of the at leastone light source remains).

As used herein the term “field of view of the LIDAR system” may broadlyinclude an extent of the observable environment of the LIDAR system inwhich objects may be detected. It is noted that the field of view (FOV)of the LIDAR system may be affected by various conditions such as butnot limited to: an orientation of the LIDAR system (e.g. is thedirection of an optical axis of the LIDAR system); a position of theLIDAR system with respect to the environment (e.g. distance above groundand adjacent topography and obstacles); operational parameters of theLIDAR system (e.g. emission power, computational settings, definedangles of operation), etc. The field of view of the LIDAR system may bedefined, for example, by a solid angle (e.g. defined using ϕ, θ angles,in which ϕ and θ are angles defined in perpendicular planes, e.g. withrespect to symmetry axes of the LIDAR system and/or its FOV). In oneexample, the field of view may also be defined within a certain range(e.g., up to 200 m).

Similarly, the term “instantaneous field of view” may broadly include anextent of the observable environment in which objects may be detected bythe LIDAR system at any given moment. For example, for a scanning LIDARsystem, the instantaneous field of view is narrower than the entire FOVof the LIDAR system, and it can be moved within the FOV of the LIDARsystem in order to enable detection in other parts of the FOV of theLIDAR system. The movement of the instantaneous field of view within theFOV of the LIDAR system may be achieved by moving a light deflector ofthe LIDAR system (or external to the LIDAR system), so as to deflectbeams of light to and/or from the LIDAR system in differing directions.In one embodiment, the LIDAR system may be configured to scan scene inthe environment in which the LIDAR system is operating. As used hereinthe term “scene” may broadly include some or all of the objects withinthe field of view of the LIDAR system, in their relative positions andin their current states, within an operational duration of the LIDARsystem. For example, the scene may include ground elements (e.g. earth,roads, grass, sidewalks, road surface marking), sky, man-made objects(e.g. vehicles, buildings, signs), vegetation, people, animals, lightprojecting elements (e.g. flashlights, sun, other LIDAR systems), and soon.

Disclosed embodiments may involve obtaining information for use ingenerating reconstructed three-dimensional models. Examples of types ofreconstructed three-dimensional models which may be used include pointcloud models, and Polygon Mesh (e.g. a triangle mesh). The terms “pointcloud” and “point cloud model” are widely known in the art, and shouldbe construed to include a set of data points located spatially in somecoordinate system (i.e., having an identifiable location in a spacedescribed by a respective coordinate system).The term “point cloudpoint” refer to a point in space (which may be dimensionless, or aminiature cellular space, e.g. 1 cm³), and whose location may bedescribed by the point cloud model using a set of coordinates (e.g.(X,Y,Z), (r, ϕ,θ)). By way of example only, the point cloud model maystore additional information for some or all of its points (e.g. colorinformation for points generated from camera images). Likewise, anyother type of reconstructed three-dimensional model may store additionalinformation for some or all of its objects. Similarly, the terms“polygon mesh” and “triangle mesh” are widely known in the art, and areto be construed to include, among other things, a set of vertices, edgesand faces that define the shape of one or more 3D objects (such as apolyhedral object). The faces may include one or more of the following:triangles (triangle mesh), quadrilaterals, or other simple convexpolygons, since this may simplify rendering. The faces may also includemore general concave polygons, or polygons with holes. Polygon meshesmay be represented using differing techniques, such as: Vertex-vertexmeshes, Face-vertex meshes, Winged-edge meshes and Render dynamicmeshes. Different portions of the polygon mesh (e.g., vertex, face,edge) are located spatially in some coordinate system (i.e., having anidentifiable location in a space described by the respective coordinatesystem), either directly and/or relative to one another. The generationof the reconstructed three-dimensional model may be implemented usingany standard, dedicated and/or novel photogrammetry technique, many ofwhich are known in the art. It is noted that other types of models ofthe environment may be generated by the LIDAR system.

Consistent with disclosed embodiments, the LIDAR system may include atleast one projecting unit with a light source configured to projectlight. As used herein the term “light source” broadly refers to anydevice configured to emit light. In one embodiment, the light source maybe a laser such as a solid-state laser, laser diode, a high power laser,or an alternative light source such as, a light emitting diode(LED)-based light source. In addition, light source 112 as illustratedthroughout the figures, may emit light in differing formats, such aslight pulses, continuous wave (CW), quasi-CW, and so on. For example,one type of light source that may be used is a vertical-cavitysurface-emitting laser (VCSEL). Another type of light source that may beused is an external cavity diode laser (ECDL). In some examples, thelight source may include a laser diode configured to emit light at awavelength between about 650 nm and 1150 nm. Alternatively, the lightsource may include a laser diode configured to emit light at awavelength between about 800 nm and about 1000 nm, between about 850 nmand about 950 nm, or between about 1300 nm and about 1600 nm. Unlessindicated otherwise, the term “about” with regards to a numeric value isdefined as a variance of up to 5% with respect to the stated value.Additional details on the projecting unit and the at least one lightsource are described below with reference to FIGS. 2A-2C.

Consistent with disclosed embodiments, the LIDAR system may include atleast one scanning unit with at least one light deflector configured todeflect light from the light source in order to scan the field of view.The term “light deflector” broadly includes any mechanism or modulewhich is configured to make light deviate from its original path; forexample, a mirror, a prism, controllable lens, a mechanical mirror,mechanical scanning polygons, active diffraction (e.g. controllableLCD), Risley prisms, non-mechanical-electro-optical beam steering (suchas made by Vscent), polarization grating (such as offered by BoulderNon-Linear Systems), optical phased array (OPA), and more. In oneembodiment, a light deflector may include a plurality of opticalcomponents, such as at least one reflecting element (e.g. a mirror), atleast one refracting element (e.g. a prism, a lens), and so on. In oneexample, the light deflector may be movable, to cause light to deviateto differing degrees (e.g. discrete degrees, or over a continuous spanof degrees). The light deflector may optionally be controllable indifferent ways (e.g. deflect to a degree a, change deflection angle byAct, move a component of the light deflector by M millimeters, changespeed in which the deflection angle changes). In addition, the lightdeflector may optionally be operable to change an angle of deflectionwithin a single plane (e.g., θ coordinate). The light deflector mayoptionally be operable to change an angle of deflection within twonon-parallel planes (e.g., θ and ϕ coordinates). Alternatively or inaddition, the light deflector may optionally be operable to change anangle of deflection between predetermined settings (e.g. along apredefined scanning route) or otherwise. With respect to the use oflight deflectors in LIDAR systems, it is noted that a light deflectormay be used in the outbound direction (also referred to as transmissiondirection, or TX) to deflect light from the light source to at least apart of the field of view. However, a light deflector may also be usedin the inbound direction (also referred to as reception direction, orRX) to deflect light from at least a part of the field of view to one ormore light sensors. Additional details on the scanning unit and the atleast one light deflector are described below with reference to FIGS.3A-3C.

Disclosed embodiments may involve pivoting the light deflector in orderto scan the field of view. As used herein the term “pivoting” broadlyincludes rotating of an object (especially a solid object) about one ormore axis of rotation, while substantially maintaining a center ofrotation fixed. In one embodiment, the pivoting of the light deflectormay include rotation of the light deflector about a fixed axis (e.g., ashaft), but this is not necessarily so. For example, in some MEMS mirrorimplementation, the MEMS mirror may move by actuation of a plurality ofbenders connected to the mirror, the mirror may experience some spatialtranslation in addition to rotation. Nevertheless, such mirror may bedesigned to rotate about a substantially fixed axis, and thereforeconsistent with the present disclosure it considered to be pivoted. Inother embodiments, some types of light deflectors (e.g.non-mechanical-electro-optical beam steering, OPA) do not require anymoving components or internal movements in order to change thedeflection angles of deflected light. It is noted that any discussionrelating to moving or pivoting a light deflector is also mutatismutandis applicable to controlling the light deflector such that itchanges a deflection behavior of the light deflector. For example,controlling the light deflector may cause a change in a deflection angleof beams of light arriving from at least one direction.

Disclosed embodiments may involve receiving reflections associated witha portion of the field of view corresponding to a single instantaneousposition of the light deflector. As used herein, the term “instantaneousposition of the light deflector” (also referred to as “state of thelight deflector”) broadly refers to the location or position in spacewhere at least one controlled component of the light deflector issituated at an instantaneous point in time, or over a short span oftime. In one embodiment, the instantaneous position of the lightdeflector may be gauged with respect to a frame of reference. The frameof reference may pertain to at least one fixed point in the LIDARsystem. Or, for example, the frame of reference may pertain to at leastone fixed point in the scene. In some embodiments, the instantaneousposition of the light deflector may include some movement of one or morecomponents of the light deflector (e.g. mirror, prism), usually to alimited degree with respect to the maximal degree of change during ascanning of the field of view. For example, a scanning of the entirefield of view of the LIDAR system may include changing deflection oflight over a span of 30°, and the instantaneous position of the at leastone light deflector may include angular shifts of the light deflectorwithin 0.05°. In other embodiments, the term “instantaneous position ofthe light deflector” may refer to the positions of the light deflectorduring acquisition of light which is processed to provide data for asingle point of a point cloud (or another type of 3D model) generated bythe LIDAR system. In some embodiments, an instantaneous position of thelight deflector may correspond with a fixed position or orientation inwhich the deflector pauses for a short time during illumination of aparticular sub-region of the LIDAR field of view. In other cases, aninstantaneous position of the light deflector may correspond with acertain position/orientation along a scanned range ofpositions/orientations of the light deflector that the light deflectorpasses through as part of a continuous or semi-continuous scan of theLIDAR field of view. In some embodiments, the light deflector may bemoved such that during a scanning cycle of the LIDAR FOV the lightdeflector is located at a plurality of different instantaneouspositions. In other words, during the period of time in which a scanningcycle occurs, the deflector may be moved through a series of differentinstantaneous positions/orientations, and the deflector may reach eachdifferent instantaneous position/orientation at a different time duringthe scanning cycle.

Consistent with disclosed embodiments, the LIDAR system may include atleast one sensing unit with at least one sensor configured to detectreflections from objects in the field of view. The term “sensor” broadlyincludes any device, element, or system capable of measuring properties(e.g., power, frequency, phase, pulse timing, pulse duration) ofelectromagnetic waves and to generate an output relating to the measuredproperties. In some embodiments, the at least one sensor may include aplurality of detectors constructed from a plurality of detectingelements. The at least one sensor may include light sensors of one ormore types. It is noted that the at least one sensor may includemultiple sensors of the same type which may differ in othercharacteristics (e.g., sensitivity, size). Other types of sensors mayalso be used. Combinations of several types of sensors can be used fordifferent reasons, such as improving detection over a span of ranges(especially in close range); improving the dynamic range of the sensor;improving the temporal response of the sensor; and improving detectionin varying environmental conditions (e.g. atmospheric temperature, rain,etc.).

In one embodiment, the at least one sensor includes a SiPM (Siliconphotomultipliers) which is a solid-state single-photon-sensitive devicebuilt from an array of avalanche photodiode (APD), single photonavalanche diode (SPAD), serving as detection elements on a commonsilicon substrate. In one example, a typical distance between SPADs maybe between about 10 μm and about 50 μm, wherein each SPAD may have arecovery time of between about 20 ns and about 100 ns. Similarphotomultipliers from other, non-silicon materials may also be used.Although a SiPM device works in digital/switching mode, the SiPM is ananalog device because all the microcells may be read in parallel, makingit possible to generate signals within a dynamic range from a singlephoton to hundreds and thousands of photons detected by the differentSPADs. It is noted that outputs from different types of sensors (e.g.,SPAD, APD, SiPM, PIN diode, Photodetector) may be combined together to asingle output which may be processed by a processor of the LIDAR system.Additional details on the sensing unit and the at least one sensor aredescribed below with reference to FIGS. 4A-4C.

Consistent with disclosed embodiments, the LIDAR system may include orcommunicate with at least one processor configured to execute differingfunctions. The at least one processor may constitute any physical devicehaving an electric circuit that performs a logic operation on input orinputs. For example, the at least one processor may include one or moreintegrated circuits (IC), including Application-specific integratedcircuit (ASIC), microchips, microcontrollers, microprocessors, all orpart of a central processing unit (CPU), graphics processing unit (GPU),digital signal processor (DSP), field-programmable gate array (FPGA), orother circuits suitable for executing instructions or performing logicoperations. The instructions executed by at least one processor may, forexample, be pre-loaded into a memory integrated with or embedded intothe controller or may be stored in a separate memory. The memory maycomprise a Random Access Memory (RAM), a Read-Only Memory (ROM), a harddisk, an optical disk, a magnetic medium, a flash memory, otherpermanent, fixed, or volatile memory, or any other mechanism capable ofstoring instructions. In some embodiments, the memory is configured tostore representative data about objects in the environment of the LIDARsystem. In some embodiments, the at least one processor may include morethan one processor. Each processor may have a similar construction orthe processors may be of differing constructions that are electricallyconnected or disconnected from each other. For example, the processorsmay be separate circuits or integrated in a single circuit. When morethan one processor is used, the processors may be configured to operateindependently or collaboratively. The processors may be coupledelectrically, magnetically, optically, acoustically, mechanically or byother means that permit them to interact. Additional details on theprocessing unit and the at least one processor are described below withreference to FIGS. 5A-5C.

System Overview

FIG. 1A illustrates a LIDAR system 100 including a projecting unit 102,a scanning unit 104, a sensing unit 106, and a processing unit 108.LIDAR system 100 may be mountable on a vehicle 110. Consistent withembodiments of the present disclosure, projecting unit 102 may includeat least one light source 112, scanning unit 104 may include at leastone light deflector 114, sensing unit 106 may include at least onesensor 116, and processing unit 108 may include at least one processor118. In one embodiment, at least one processor 118 may be configured tocoordinate operation of the at least one light source 112 with themovement of at least one light deflector 114 in order to scan a field ofview 120. During a scanning cycle, each instantaneous position of atleast one light deflector 114 may be associated with a particularportion 122 of field of view 120. In addition, LIDAR system 100 mayinclude at least one optional optical window 124 for directing lightprojected towards field of view 120 and/or receiving light reflectedfrom objects in field of view 120. Optional optical window 124 may servedifferent purposes, such as collimation of the projected light andfocusing of the reflected light. In one embodiment, optional opticalwindow 124 may be an opening, a flat window, a lens, or any other typeof optical window.

Consistent with the present disclosure, LIDAR system 100 may be used inautonomous or semi-autonomous road-vehicles (for example, cars, buses,vans, trucks and any other terrestrial vehicle). Autonomousroad-vehicles with LIDAR system 100 may scan their environment and driveto a destination without human input. Similarly, LIDAR system 100 mayalso be used in autonomous/semi-autonomous aerial-vehicles (for example,UAV, drones, quadcopters, and any other airborne vehicle or device); orin an autonomous or semi-autonomous water vessel (e.g., boat, ship,submarine, or any other watercraft). Autonomous aerial-vehicles andwater craft with LIDAR system 100 may scan their environment andnavigate to a destination autonomously or using a remote human operator.According to one embodiment, vehicle 110 (either a road-vehicle,aerial-vehicle, or watercraft) may use LIDAR system 100 to aid indetecting and scanning the environment in which vehicle 110 isoperating.

It should be noted that LIDAR system 100 or any of its components may beused together with any of the example embodiments and methods disclosedherein. Further, while some aspects of LIDAR system 100 are describedrelative to an exemplary vehicle-based LIDAR platform, LIDAR system 100,any of its components, or any of the processes described herein may beapplicable to LIDAR systems of other platform types.

In some embodiments, LIDAR system 100 may include one or more scanningunits 104 to scan the environment around vehicle 110. LIDAR system 100may be attached or mounted to any part of vehicle 110. Sensing unit 106may receive reflections from the surroundings of vehicle 110, andtransfer reflection signals indicative of light reflected from objectsin field of view 120 to processing unit 108. Consistent with the presentdisclosure, scanning units 104 may be mounted to or incorporated into abumper, a fender, a side panel, a spoiler, a roof, a headlight assembly,a taillight assembly, a rear-view mirror assembly, a hood, a trunk orany other suitable part of vehicle 110 capable of housing at least aportion of the LIDAR system. In some cases, LIDAR system 100 may capturea complete surround view of the environment of vehicle 110. Thus, LIDARsystem 100 may have a 360-degree horizontal field of view. In oneexample, as shown in FIG. 1A, LIDAR system 100 may include a singlescanning unit 104 mounted on a roof of vehicle 110. Alternatively, LIDARsystem 100 may include multiple scanning units (e.g., two, three, four,or more scanning units 104) each with a field of view such that in theaggregate the horizontal field of view is covered by a 360-degree scanaround vehicle 110. One skilled in the art will appreciate that LIDARsystem 100 may include any number of scanning units 104 arranged in anymanner, each with an 80° to 120° field of view or less, depending on thenumber of units employed. Moreover, a 360-degree horizontal field ofview may be also obtained by mounting multiple LIDAR systems 100 onvehicle 110, each with a single scanning unit 104. It is neverthelessnoted, that the one or more LIDAR systems 100 do not have to provide acomplete 360° field of view, and that narrower fields of view may beuseful in some situations. For example, vehicle 110 may require a firstLIDAR system 100 having an field of view of 75° looking ahead of thevehicle, and possibly a second LIDAR system 100 with a similar FOVlooking backward (optionally with a lower detection range). It is alsonoted that different vertical field of view angles may also beimplemented.

FIG. 1B is an image showing an exemplary output from a single scanningcycle of LIDAR system 100 mounted on vehicle 110 consistent withdisclosed embodiments. In this example, scanning unit 104 isincorporated into a right headlight assembly of vehicle 110. Every graydot in the image corresponds to a location in the environment aroundvehicle 110 determined from reflections detected by sensing unit 106. Inaddition to location, each gray dot may also be associated withdifferent types of information, for example, intensity (e.g., how muchlight returns back from that location), reflectivity, proximity to otherdots, and more. In one embodiment, LIDAR system 100 may generate aplurality of point-cloud data entries from detected reflections ofmultiple scanning cycles of the field of view to enable, for example,determining a point cloud model of the environment around vehicle 110.

FIG. 1C is an image showing a representation of the point cloud modeldetermined from the output of LIDAR system 100. Consistent withdisclosed embodiments, by processing the generated point-cloud dataentries of the environment around vehicle 110, a surround-view image maybe produced from the point cloud model. In one embodiment, the pointcloud model may be provided to a feature extraction module, whichprocesses the point cloud information to identify a plurality offeatures. Each feature may include data about different aspects of thepoint cloud and/or of objects in the environment around vehicle 110(e.g. cars, trees, people, and roads). Features may have the sameresolution of the point cloud model (i.e. having the same number of datapoints, optionally arranged into similar sized 2D arrays), or may havedifferent resolutions. The features may be stored in any kind of datastructure (e.g. raster, vector, 2D array, 1D array). In addition,virtual features, such as a representation of vehicle 110, border lines,or bounding boxes separating regions or objects in the image (e.g., asdepicted in FIG. 1B), and icons representing one or more identifiedobjects, may be overlaid on the representation of the point cloud modelto form the final surround-view image. For example, a symbol of vehicle110 may be overlaid at a center of the surround-view image.

The Projecting Unit

FIGS. 2A-2G depict various configurations of projecting unit 102 and itsrole in LIDAR system 100. Specifically, FIG. 2A is a diagramillustrating projecting unit 102 with a single light source; FIG. 2B isa diagram illustrating a plurality of projecting units 102 with aplurality of light sources aimed at a common light deflector 114; FIG.2C is a diagram illustrating projecting unit 102 with a primary and asecondary light sources 112; FIG. 2D is a diagram illustrating anasymmetrical deflector used in some configurations of projecting unit102; FIG. 2E is a diagram illustrating a first configuration of anon-scanning LIDAR system; FIG. 2F is a diagram illustrating a secondconfiguration of a non-scanning LIDAR system; and FIG. 2G is a diagramillustrating a LIDAR system that scans in the outbound direction anddoes not scan in the inbound direction. One skilled in the art willappreciate that the depicted configurations of projecting unit 102 mayhave numerous variations and modifications.

FIG. 2A illustrates an example of a bi-static configuration of LIDARsystem 100 in which projecting unit 102 includes a single light source112. The term “bi-static configuration” broadly refers to LIDAR systemsconfigurations in which the projected light exiting the LIDAR system andthe reflected light entering the LIDAR system pass through substantiallydifferent optical paths. In some embodiments, a bi-static configurationof LIDAR system 100 may include a separation of the optical paths byusing completely different optical components, by using parallel but notfully separated optical components, or by using the same opticalcomponents for only part of the of the optical paths (optical componentsmay include, for example, windows, lenses, mirrors, beam splitters,etc.). In the example depicted in FIG. 2A, the bi-static configurationincludes a configuration where the outbound light and the inbound lightpass through a single optical window 124 but scanning unit 104 includestwo light deflectors, a first light deflector 114A for outbound lightand a second light deflector 114B for inbound light (the inbound lightin LIDAR system includes emitted light reflected from objects in thescene, and may also include ambient light arriving from other sources).In the examples depicted in FIGS. 2E and 2G, the bi-static configurationincludes a configuration where the outbound light passes through a firstoptical window 124A, and the inbound light passes through a secondoptical window 124B. In all the example configurations above, theinbound and outbound optical paths differ from one another.

In this embodiment, all the components of LIDAR system 100 may becontained within a single housing 200, or may be divided among aplurality of housings. As shown, projecting unit 102 is associated witha single light source 112 that includes a laser diode 202A (or two ormore laser diodes coupled together) configured to emit light (projectedlight 204). In one non-limiting example, the light projected by lightsource 112 may be at a wavelength between about 800 nm and 950 nm, havean average power between about 50 mW and about 500 mW, have a peak powerbetween about 50 W and about 200 W, and a pulse width of between about 2ns and about 100 ns. In addition, light source 112 may optionally beassociated with optical assembly 202B used for manipulation of the lightemitted by laser diode 202A (e.g. for collimation, focusing, etc.). Itis noted that other types of light sources 112 may be used, and that thedisclosure is not restricted to laser diodes. In addition, light source112 may emit its light in different formats, such as light pulses,frequency modulated, continuous wave (CW), quasi-CW, or any other formcorresponding to the particular light source employed. The projectionformat and other parameters may be changed by the light source from timeto time based on different factors, such as instructions from processingunit 108. The projected light is projected towards an outbound deflector114A that functions as a steering element for directing the projectedlight in field of view 120. In this example, scanning unit 104 may alsoinclude a pivotable return deflector 114B that directs photons(reflected light 206) reflected back from an object 208 within field ofview 120 toward sensor 116. The reflected light is detected by sensor116 and information about the object (e.g., the distance to object 212)is determined by processing unit 108.

In this figure, LIDAR system 100 is connected to a host 210. Consistentwith the present disclosure, the term “host” refers to any computingenvironment that may interface with LIDAR system 100, it may be avehicle system (e.g., part of vehicle 110), a testing system, a securitysystem, a surveillance system, a traffic control system, an urbanmodelling system, or any system that monitors its surroundings. Such acomputing environment may include at least one processor and/or may beconnected to LIDAR system 100 via the cloud. In some embodiments, host210 may also include interfaces to external devices such as a camera andsensors configured to measure different characteristics of host 210(e.g., acceleration, steering wheel deflection, reverse drive, etc.).Consistent with the present disclosure, LIDAR system 100 may be fixed toa stationary object associated with host 210 (e.g. a building, a tripod)or to a portable system associated with host 210 (e.g., a portablecomputer, a movie camera). Consistent with the present disclosure, LIDARsystem 100 may be connected to host 210, to provide outputs of LIDARsystem 100 (e.g., a 3D model, a reflectivity image) to host 210.Specifically, host 210 may use LIDAR system 100 to aid in detecting andscanning the environment of host 210 or any other environment. Inaddition, host 210 may integrate, synchronize or otherwise use togetherthe outputs of LIDAR system 100 with outputs of other sensing systems(e.g. cameras, microphones, radar systems). In one example, LIDAR system100 may be used by a security system.

LIDAR system 100 may also include a bus 212 (or other communicationmechanisms) that interconnect subsystems and components for transferringinformation within LIDAR system 100. Optionally, bus 212 (or anothercommunication mechanism) may be used for interconnecting LIDAR system100 with host 210. In the example of FIG. 2A, processing unit 108includes two processors 118 to regulate the operation of projecting unit102, scanning unit 104, and sensing unit 106 in a coordinated mannerbased, at least partially, on information received from internalfeedback of LIDAR system 100. In other words, processing unit 108 may beconfigured to dynamically operate LIDAR system 100 in a closed loop. Aclosed loop system is characterized by having feedback from at least oneof the elements and updating one or more parameters based on thereceived feedback. Moreover, a closed loop system may receive feedbackand update its own operation, at least partially, based on thatfeedback. A dynamic system or element is one that may be updated duringoperation.

According to some embodiments, scanning the environment around LIDARsystem 100 may include illuminating field of view 120 with light pulses.The light pulses may have parameters such as: pulse duration, pulseangular dispersion, wavelength, instantaneous power, photon density atdifferent distances from light source 112, average power, pulse powerintensity, pulse width, pulse repetition rate, pulse sequence, pulseduty cycle, wavelength, phase, polarization, and more. Scanning theenvironment around LIDAR system 100 may also include detecting andcharacterizing various aspects of the reflected light. Characteristicsof the reflected light may include, for example: time-of-flight (i.e.,time from emission until detection), instantaneous power (e.g., powersignature), average power across entire return pulse, and photondistribution/signal over return pulse period. By comparingcharacteristics of a light pulse with characteristics of correspondingreflections, a distance and possibly a physical characteristic, such asreflected intensity of object 212 may be estimated. By repeating thisprocess across multiple adjacent portions 122, in a predefined pattern(e.g., raster, Lissajous or other patterns) an entire scan of field ofview 120 may be achieved. As discussed below in greater detail, in somesituations LIDAR system 100 may direct light to only some of theportions 122 in field of view 120 at every scanning cycle. Theseportions may be adjacent to each other, but not necessarily so.

In another embodiment, LIDAR system 100 may include network interface214 for communicating with host 210 (e.g., a vehicle controller). Thecommunication between LIDAR system 100 and host 210 is represented by adashed arrow. In one embodiment, network interface 214 may include anintegrated services digital network (ISDN) card, cable modem, satellitemodem, or a modem to provide a data communication connection to acorresponding type of telephone line. As another example, networkinterface 214 may include a local area network (LAN) card to provide adata communication connection to a compatible LAN. In anotherembodiment, network interface 214 may include an Ethernet port connectedto radio frequency receivers and transmitters and/or optical (e.g.,infrared) receivers and transmitters. The specific design andimplementation of network interface 214 depends on the communicationsnetwork(s) over which LIDAR system 100 and host 210 are intended tooperate. For example, network interface 214 may be used, for example, toprovide outputs of LIDAR system 100 to the external system, such as a 3Dmodel, operational parameters of LIDAR system 100, and so on. In otherembodiment, the communication unit may be used, for example, to receiveinstructions from the external system, to receive information regardingthe inspected environment, to receive information from another sensor,etc.

FIG. 2B illustrates an example of a monostatic configuration of LIDARsystem 100 including a plurality of projecting units 102. The term“monostatic configuration” broadly refers to LIDAR system configurationsin which the projected light exiting from the LIDAR system and thereflected light entering the LIDAR system pass through substantiallysimilar optical paths. In one example, the outbound light beam and theinbound light beam may share at least one optical assembly through whichboth outbound and inbound light beams pass. In another example, theoutbound light may pass through an optical window (not shown) and theinbound light radiation may pass through the same optical window. Amonostatic configuration may include a configuration where the scanningunit 104 includes a single light deflector 114 that directs theprojected light towards field of view 120 and directs the reflectedlight towards a sensor 116. As shown, both projected light 204 andreflected light 206 hit an asymmetrical deflector 216. The term“asymmetrical deflector” refers to any optical device having two sidescapable of deflecting a beam of light hitting it from one side in adifferent direction than it deflects a beam of light hitting it from thesecond side. In one example, the asymmetrical deflector does not deflectprojected light 204 and deflects reflected light 206 towards sensor 116.One example of an asymmetrical deflector may include a polarization beamsplitter. In another example, asymmetrical deflector 216 may include anoptical isolator that allows the passage of light in only one direction.A diagrammatic representation of asymmetrical deflector 216 isillustrated in FIG. 2D. Consistent with the present disclosure, amonostatic configuration of LIDAR system 100 may include an asymmetricaldeflector to prevent reflected light from hitting light source 112, andto direct all the reflected light toward sensor 116, thereby increasingdetection sensitivity.

In the embodiment of FIG. 2B, LIDAR system 100 includes three projectingunits 102 each with a single light source 112 aimed at a common lightdeflector 114. In one embodiment, the plurality of light sources 112(including two or more light sources) may project light withsubstantially the same wavelength and each light source 112 is generallyassociated with a differing area of the field of view (denoted in thefigure as 120A, 120B, and 120C). This enables scanning of a broaderfield of view than can be achieved with a light source 112. In anotherembodiment, the plurality of light sources 102 may project light withdiffering wavelengths, and all the light sources 112 may be directed tothe same portion (or overlapping portions) of field of view 120.

FIG. 2C illustrates an example of LIDAR system 100 in which projectingunit 102 includes a primary light source 112A and a secondary lightsource 112B. Primary light source 112A may project light with a longerwavelength to which the human eye is not sensitive in order to optimizeSNR and detection range. For example, primary light source 112A mayproject light with a wavelength between about 750 nm and 1100 nm. Incontrast, secondary light source 112B may project light with awavelength visible to the human eye. For example, secondary light source112B may project light with a wavelength between about 400 nm and 700nm. In one embodiment, secondary light source 112B may project lightalong substantially the same optical path as the light projected byprimary light source 112A. Both light sources may be time-synchronizedand may project light emission together or in interleaved pattern. Aninterleave pattern means that the light sources are not active at thesame time which may mitigate mutual interference. A person who is ofskill in the art would readily see that other combinations of wavelengthranges and activation schedules may also be implemented.

Consistent with some embodiments, secondary light source 112B may causehuman eyes to blink when it is too close to the LIDAR optical outputport. This may ensure an eye safety mechanism not feasible with typicallaser sources that utilize the near-infrared light spectrum. In anotherembodiment, secondary light source 112B may be used for calibration andreliability at a point of service, in a manner somewhat similar to thecalibration of headlights with a special reflector/pattern at a certainheight from the ground with respect to vehicle 110. An operator at apoint of service could examine the calibration of the LIDAR by simplevisual inspection of the scanned pattern over a featured target such atest pattern board at a designated distance from LIDAR system 100. Inaddition, secondary light source 112B may provide means for operationalconfidence that the LIDAR is working for the end-user. For example, thesystem may be configured to permit a human to place a hand in front oflight deflector 114 to test its operation.

Secondary light source 112B may also have a non-visible element that candouble as a backup system in case primary light source 112A fails. Thisfeature may be useful for fail-safe devices with elevated functionalsafety ratings. Given that secondary light source 112B may be visibleand also due to reasons of cost and complexity, secondary light source112B may be associated with a smaller power compared to primary lightsource 112A. Therefore, in case of a failure of primary light source112A, the system functionality will rely on the functionalities andcapabilities of the secondary light source 112B. While the capabilitiesof secondary light source 112B may be inferior to the capabilities ofprimary light source 112A, LIDAR system 100 may be designed in such afashion to enable vehicle 110 to safely arrive at its destination.

FIG. 2D illustrates asymmetrical deflector 216 that may be part of LIDARsystem 100. In the illustrated example, asymmetrical deflector 216includes a reflective surface 218 (such as a mirror) and a one-waydeflector 220. While not necessarily so, asymmetrical deflector 216 mayoptionally be a static deflector. Asymmetrical deflector 216 may be usedin a monostatic configuration of LIDAR system 100, in order to allow acommon optical path for transmission and for reception of light via theat least one deflector 114, e.g. as illustrated in FIGS. 2B and 2C.However, typical asymmetrical deflectors such as beam splitters arecharacterized by energy losses, especially in the reception path, whichmay be more sensitive to power loses than the transmission path.

As depicted in FIG. 2D, LIDAR system 100 may include asymmetricaldeflector 216 positioned in the transmission path, which includesone-way deflector 220 for separating between the transmitted andreceived light signals. Optionally, one-way deflector 220 may besubstantially transparent to the transmission light and substantiallyreflective to the received light. The transmitted light is generated byprojecting unit 102 and may travel through one-way deflector 220 toscanning unit 104 which deflects it towards the optical outlet. Thereceived light arrives through the optical inlet, to the at least onedeflecting element 114, which deflects the reflections signal into aseparate path away from the light source and towards sensing unit 106.Optionally, asymmetrical deflector 216 may be combined with a polarizedlight source 112 which is linearly polarized with the same polarizationaxis as one-way deflector 220. Notably, the cross-section of theoutbound light beam is much smaller than that of the reflectionssignals. Accordingly, LIDAR system 100 may include one or more opticalcomponents (e.g. lens, collimator) for focusing or otherwisemanipulating the emitted polarized light beam to the dimensions of theasymmetrical deflector 216. In one embodiment, one-way deflector 220 maybe a polarizing beam splitter that is virtually transparent to thepolarized light beam.

Consistent with some embodiments, LIDAR system 100 may further includeoptics 222 (e.g., a quarter wave plate retarder) for modifying apolarization of the emitted light. For example, optics 222 may modify alinear polarization of the emitted light beam to circular polarization.Light reflected back to system 100 from the field of view would arriveback through deflector 114 to optics 222, bearing a circularpolarization with a reversed handedness with respect to the transmittedlight. Optics 222 would then convert the received reversed handednesspolarization light to a linear polarization that is not on the same axisas that of the polarized beam splitter 216. As noted above, the receivedlight-patch is larger than the transmitted light-patch, due to opticaldispersion of the beam traversing through the distance to the target.

Some of the received light will impinge on one-way deflector 220 thatwill reflect the light towards sensor 106 with some power loss. However,another part of the received patch of light will fall on a reflectivesurface 218 which surrounds one-way deflector 220 (e.g., polarizing beamsplitter slit). Reflective surface 218 will reflect the light towardssensing unit 106 with substantially zero power loss. One-way deflector220 would reflect light that is composed of various polarization axesand directions that will eventually arrive at the detector. Optionally,sensing unit 106 may include sensor 116 that is agnostic to the laserpolarization, and is primarily sensitive to the amount of impingingphotons at a certain wavelength range.

It is noted that the proposed asymmetrical deflector 216 provides farsuperior performance when compared to a simple mirror with a passagehole in it. In a mirror with a hole, all of the reflected light whichreaches the hole is lost to the detector. However, in deflector 216,one-way deflector 220 deflects a significant portion of that light(e.g., about 50%) toward the respective sensor 116. In LIDAR systems,the number of photons reaching the LIDAR from remote distances is verylimited, and therefore the improvement in photon capture rate isimportant.

According to some embodiments, a device for beam splitting and steeringis described. A polarized beam may be emitted from a light source havinga first polarization. The emitted beam may be directed to pass through apolarized beam splitter assembly. The polarized beam splitter assemblyincludes on a first side a one-directional slit and on an opposing sidea mirror. The one-directional slit enables the polarized emitted beam totravel toward a quarter-wave-plate/wave-retarder which changes theemitted signal from a circular polarization signal to a linearpolarization signal (or vice versa) so that subsequently reflected beamscannot travel through the one-directional slit.

FIG. 2E shows an example of a bi-static configuration of LIDAR system100 without scanning unit 104. In order to illuminate an entire field ofview (or substantially the entire field of view) without deflector 114,projecting unit 102 may optionally include an array of light sources(e.g., 112A-112F). In one embodiment, the array of light sources mayinclude a linear array of light sources controlled by processor 118. Forexample, processor 118 may cause the linear array of light sources tosequentially project collimated laser beams towards first optionaloptical window 124A. First optional optical window 124A may include adiffuser lens for spreading the projected light and sequentially formingwide horizontal and narrow vertical beams. Optionally, some or all ofthe at least one light source 112 of system 100 may project lightconcurrently. For example, processor 118 may cause the array of lightsources to simultaneously project light beams from a plurality ofnon-adjacent light sources 112. In the depicted example, light source112A, light source 112D, and light source 112F simultaneously projectlaser beams towards first optional optical window 124A therebyilluminating the field of view with three narrow vertical beams. Thelight beam from fourth light source 112D may reach an object in thefield of view. The light reflected from the object may be captured bysecond optical window 124B and may be redirected to sensor 116. Theconfiguration depicted in FIG. 2E is considered to be a bi-staticconfiguration because the optical paths of the projected light and thereflected light are substantially different. It is noted that projectingunit 102 may also include a plurality of light sources 112 arranged innon-linear configurations, such as a two dimensional array, in hexagonaltiling, or in any other way.

FIG. 2F illustrates an example of a monostatic configuration of LIDARsystem 100 without scanning unit 104. Similar to the example embodimentrepresented in FIG. 2E, in order to illuminate an entire field of viewwithout deflector 114, projecting unit 102 may include an array of lightsources (e.g., 112A-112F). But, in contrast to FIG. 2E, thisconfiguration of LIDAR system 100 may include a single optical window124 for both the projected light and for the reflected light. Usingasymmetrical deflector 216, the reflected light may be redirected tosensor 116. The configuration depicted in FIG. 2E is considered to be amonostatic configuration because the optical paths of the projectedlight and the reflected light are substantially similar to one another.The term “substantially similar” in the context of the optical paths ofthe projected light and the reflected light means that the overlapbetween the two optical paths may be more than 80%, more than 85%, morethan 90%, or more than 95%.

FIG. 2G illustrates an example of a bi-static configuration of LIDARsystem 100. The configuration of LIDAR system 100 in this figure issimilar to the configuration shown in FIG. 2A. For example, bothconfigurations include a scanning unit 104 for directing projected lightin the outbound direction toward the field of view. But, in contrast tothe embodiment of FIG. 2A, in this configuration, scanning unit 104 doesnot redirect the reflected light in the inbound direction. Instead thereflected light passes through second optical window 124B and enterssensor 116. The configuration depicted in FIG. 2G is considered to be abi-static configuration because the optical paths of the projected lightand the reflected light are substantially different from one another.The term “substantially different” in the context of the optical pathsof the projected light and the reflected light means that the overlapbetween the two optical paths may be less than 10%, less than 5%, lessthan 1%, or less than 0.25%.

The Scanning Unit

FIGS. 3A-3D depict various configurations of scanning unit 104 and itsrole in LIDAR system 100. Specifically, FIG. 3A is a diagramillustrating scanning unit 104 with a MEMS mirror (e.g., square shaped),FIG. 3B is a diagram illustrating another scanning unit 104 with a MEMSmirror (e.g., round shaped), FIG. 3C is a diagram illustrating scanningunit 104 with an array of reflectors used for monostatic scanning LIDARsystem, and FIG. 3D is a diagram illustrating an example LIDAR system100 that mechanically scans the environment around LIDAR system 100. Oneskilled in the art will appreciate that the depicted configurations ofscanning unit 104 are exemplary only, and may have numerous variationsand modifications within the scope of this disclosure.

FIG. 3A illustrates an example scanning unit 104 with a single axissquare MEMS mirror 300. In this example MEMS mirror 300 functions as atleast one deflector 114. As shown, scanning unit 104 may include one ormore actuators 302 (specifically, 302A and 302B). In one embodiment,actuator 302 may be made of semiconductor (e.g., silicon) and includes apiezoelectric layer (e.g. PZT, Lead zirconate titanate, aluminumnitride), which changes its dimension in response to electric signalsapplied by an actuation controller, a semi conductive layer, and a baselayer. In one embodiment, the physical properties of actuator 302 maydetermine the mechanical stresses that actuator 302 experiences whenelectrical current passes through it. When the piezoelectric material isactivated it exerts force on actuator 302 and causes it to bend. In oneembodiment, the resistivity of one or more actuators 302 may be measuredin an active state (Ractive) when mirror 300 is deflected at a certainangular position and compared to the resistivity at a resting state(Rrest). Feedback including Ractive may provide information to determinethe actual mirror deflection angle compared to an expected angle, and,if needed, mirror 300 deflection may be corrected. The differencebetween Rrest and Ractive may be correlated by a mirror drive into anangular deflection value that may serve to close the loop. Thisembodiment may be used for dynamic tracking of the actual mirrorposition and may optimize response, amplitude, deflection efficiency,and frequency for both linear mode and resonant mode MEMS mirrorschemes.

During scanning, current (represented in the figure as the dashed line)may flow from contact 304A to contact 304B (through actuator 302A,spring 306A, mirror 300, spring 306B, and actuator 302B). Isolation gapsin semiconducting frame 308 such as isolation gap 310 may cause actuator302A and 302B to be two separate islands connected electrically throughsprings 306 and frame 308. The current flow, or any associatedelectrical parameter (voltage, current, frequency, capacitance, relativedielectric constant, etc.), may be controlled based on an associatedscanner position feedback. In case of a mechanical failure—where one ofthe components is damaged—the current flow through the structure wouldalter and change from its functional calibrated values. At an extremesituation (for example, when a spring is broken), the current would stopcompletely due to a circuit break in the electrical chain by means of afaulty element.

FIG. 3B illustrates another example scanning unit 104 with a dual axisround MEMS mirror 300. In this example MEMS mirror 300 functions as atleast one deflector 114. In one embodiment, MEMS mirror 300 may have adiameter of between about 1 mm to about 5 mm. As shown, scanning unit104 may include four actuators 302 (302A, 302B, 302C, and 302D) each maybe at a differing length. In the illustrated example, the current(represented in the figure as the dashed line) flows from contact 304Ato contact 304D, but in other cases current may flow from contact 304Ato contact 304B, from contact 304A to contact 304C, from contact 304B tocontact 304C, from contact 304B to contact 304D, or from contact 304C tocontact 304D. Consistent with some embodiments, a dual axis MEMS mirrormay be configured to deflect light in a horizontal direction and in avertical direction. For example, the angles of deflection of a dual axisMEMS mirror may be between about 0° to 30° in the vertical direction andbetween about 0° to 50° in the horizontal direction. One skilled in theart will appreciate that the depicted configuration of mirror 300 mayhave numerous variations and modifications. In one example, at least onedeflector 114 may have a dual axis square-shaped mirror or single axisround-shaped mirror. Examples of round and square mirror are depicted inFIG. 3A and 3B as examples only. Any shape may be employed depending onsystem specifications. In one embodiment, actuators 302 may beincorporated as an integral part of at least one deflector 114, suchthat power to move MEMS mirror 300 is applied directly towards it. Inaddition, MEMS mirror 300 may be connected to frame 308 by one or morerigid supporting elements. In another embodiment, at least one deflector114 may include an electrostatic or electromagnetic MEMS mirror.

As described above, a monostatic scanning LIDAR system utilizes at leasta portion of the same optical path for emitting projected light 204 andfor receiving reflected light 206. The light beam in the outbound pathmay be collimated and focused into a narrow beam while the reflectionsin the return path spread into a larger patch of light, due todispersion. In one embodiment, scanning unit 104 may have a largereflection area in the return path and asymmetrical deflector 216 thatredirects the reflections (i.e., reflected light 206) to sensor 116. Inone embodiment, scanning unit 104 may include a MEMS mirror with a largereflection area and negligible impact on the field of view and the framerate performance.

In some embodiments (e.g. as exemplified in FIG. 3C), scanning unit 104may include a deflector array (e.g. a reflector array) with small lightdeflectors (e.g. mirrors). In one embodiment, implementing lightdeflector 114 as a group of smaller individual light deflectors workingin synchronization may allow light deflector 114 to perform at a highscan rate with larger angles of deflection. The deflector array mayessentially act as a large light deflector (e.g. a large mirror) interms of effective area. The deflector array may be operated using ashared steering assembly configuration that allows sensor 116 to collectreflected photons from substantially the same portion of field of view120 being concurrently illuminated by light source 112. The term“concurrently” means that the two selected functions occur duringcoincident or overlapping time periods, either where one begins and endsduring the duration of the other, or where a later one starts before thecompletion of the other.

FIG. 3C illustrates an example of scanning unit 104 with a reflectorarray 312 having small mirrors. In this embodiment, reflector array 312functions as at least one deflector 114. Reflector array 312 may includea plurality of reflector units 314 configured to pivot (individually ortogether) and steer light pulses toward field of view 120. For example,reflector array 312 may be a part of an outbound path of light projectedfrom light source 112. Specifically, reflector array 312 may directprojected light 204 towards a portion of field of view 120. Reflectorarray 312 may also be part of a return path for light reflected from asurface of an object located within an illumined portion of field ofview 120. Specifically, reflector array 312 may direct reflected light206 towards sensor 116 or towards asymmetrical deflector 216. In oneexample, the area of reflector array 312 may be between about 75 toabout 150 mm², where each reflector units 314 may have a width of about10 μm and the supporting structure may be lower than 100 μm.

According to some embodiments, reflector array 312 may include one ormore sub-groups of steerable deflectors. Each sub-group of electricallysteerable deflectors may include one or more deflector units, such asreflector unit 314. For example, each steerable deflector unit 314 mayinclude at least one of a MEMS mirror, a reflective surface assembly,and an electromechanical actuator. In one embodiment, each reflectorunit 314 may be individually controlled by an individual processor (notshown), such that it may tilt towards a specific angle along each of oneor two separate axes. Alternatively, reflector array 312 may beassociated with a common controller (e.g., processor 118) configured tosynchronously manage the movement of reflector units 314 such that atleast part of them will pivot concurrently and point in approximatelythe same direction.

In addition, at least one processor 118 may select at least onereflector unit 314 for the outbound path (referred to hereinafter as “TXMirror”) and a group of reflector units 314 for the return path(referred to hereinafter as “RX Mirror”). Consistent with the presentdisclosure, increasing the number of TX Mirrors may increase a reflectedphotons beam spread. Additionally, decreasing the number of RX Mirrorsmay narrow the reception field and compensate for ambient lightconditions (such as clouds, rain, fog, extreme heat, and otherenvironmental conditions) and improve the signal to noise ratio. Also,as indicated above, the emitted light beam is typically narrower thanthe patch of reflected light, and therefore can be fully deflected by asmall portion of the deflection array. Moreover, it is possible to blocklight reflected from the portion of the deflection array used fortransmission (e.g. the TX mirror) from reaching sensor 116, therebyreducing an effect of internal reflections of the LIDAR system 100 onsystem operation. In addition, at least one processor 118 may pivot oneor more reflector units 314 to overcome mechanical impairments anddrifts due, for example, to thermal and gain effects. In an example, oneor more reflector units 314 may move differently than intended(frequency, rate, speed etc.) and their movement may be compensated forby electrically controlling the deflectors appropriately.

FIG. 3D illustrates an exemplary LIDAR system 100 that mechanicallyscans the environment of LIDAR system 100. In this example, LIDAR system100 may include a motor or other mechanisms for rotating housing 200about the axis of the LIDAR system 100. Alternatively, the motor (orother mechanism) may mechanically rotate a rigid structure of LIDARsystem 100 on which one or more light sources 112 and one or moresensors 116 are installed, thereby scanning the environment. Asdescribed above, projecting unit 102 may include at least one lightsource 112 configured to project light emission. The projected lightemission may travel along an outbound path towards field of view 120.Specifically, the projected light emission may be reflected by deflector114A through an exit aperture 314 when projected light 204 travelstowards optional optical window 124. The reflected light emission maytravel along a return path from object 208 towards sensing unit 106. Forexample, the reflected light 206 may be reflected by deflector 114B whenreflected light 206 travels towards sensing unit 106. A person skilledin the art would appreciate that a LIDAR system with a rotationmechanism for synchronically rotating multiple light sources or multiplesensors, may use this synchronized rotation instead of (or in additionto) steering an internal light deflector.

In embodiments in which the scanning of field of view 120 is mechanical,the projected light emission may be directed to exit aperture 314 thatis part of a wall 316 separating projecting unit 102 from other parts ofLIDAR system 100. In some examples, wall 316 can be formed from atransparent material (e.g., glass) coated with a reflective material toform deflector 114B. In this example, exit aperture 314 may correspondto the portion of wall 316 that is not coated by the reflectivematerial. Additionally or alternatively, exit aperture 314 may include ahole or cut-away in the wall 316. Reflected light 206 may be reflectedby deflector 114B and directed towards an entrance aperture 318 ofsensing unit 106. In some examples, an entrance aperture 318 may includea filtering window configured to allow wavelengths in a certainwavelength range to enter sensing unit 106 and attenuate otherwavelengths. The reflections of object 208 from field of view 120 may bereflected by deflector 114B and hit sensor 116. By comparing severalproperties of reflected light 206 with projected light 204, at least oneaspect of object 208 may be determined. For example, by comparing a timewhen projected light 204 was emitted by light source 112 and a time whensensor 116 received reflected light 206, a distance between object 208and LIDAR system 100 may be determined. In some examples, other aspectsof object 208, such as shape, color, material, etc. may also bedetermined.

In some examples, the LIDAR system 100 (or part thereof, including atleast one light source 112 and at least one sensor 116) may be rotatedabout at least one axis to determine a three-dimensional map of thesurroundings of the LIDAR system 100. For example, the LIDAR system 100may be rotated about a substantially vertical axis as illustrated byarrow 320 in order to scan field of 120. Although FIG. 3D illustratesthat the LIDAR system 100 is rotated clockwise about the axis asillustrated by the arrow 320, additionally or alternatively, the LIDARsystem 100 may be rotated in a counter clockwise direction. In someexamples, the LIDAR system 100 may be rotated 360 degrees about thevertical axis. In other examples, the LIDAR system 100 may be rotatedback and forth along a sector smaller than 360-degree of the LIDARsystem 100. For example, the LIDAR system 100 may be mounted on aplatform that wobbles back and forth about the axis without making acomplete rotation.

The Sensing Unit

FIGS. 4A-4E depict various configurations of sensing unit 106 and itsrole in LIDAR system 100. Specifically, FIG. 4A is a diagramillustrating an example sensing unit 106 with a detector array, FIG. 4Bis a diagram illustrating monostatic scanning using a two-dimensionalsensor, FIG. 4C is a diagram illustrating an example of atwo-dimensional sensor 116, FIG. 4D is a diagram illustrating a lensarray associated with sensor 116, and FIG. 4E includes three diagramsillustrating the lens structure. One skilled in the art will appreciatethat the depicted configurations of sensing unit 106 are exemplary onlyand may have numerous alternative variations and modificationsconsistent with the principles of this disclosure.

FIG. 4A illustrates an example of sensing unit 106 with detector array400. In this example, at least one sensor 116 includes detector array400. LIDAR system 100 is configured to detect objects (e.g., bicycle208A and cloud 208B) in field of view 120 located at different distancesfrom LIDAR system 100 (could be meters or more). Objects 208 may be asolid object (e.g. a road, a tree, a car, a person), fluid object (e.g.fog, water, atmosphere particles), or object of another type (e.g. dustor a powdery illuminated object). When the photons emitted from lightsource 112 hit object 208 they either reflect, refract, or get absorbed.Typically, as shown in the figure, only a portion of the photonsreflected from object 208A enters optional optical window 124. As each˜15 cm change in distance results in a travel time difference of 1 ns(since the photons travel at the speed of light to and from object 208),the time differences between the travel times of different photonshitting the different objects may be detectable by a time-of-flightsensor with sufficiently quick response.

Sensor 116 includes a plurality of detection elements 402 for detectingphotons of a photonic pulse reflected back from field of view 120. Thedetection elements may all be included in detector array 400, which mayhave a rectangular arrangement (e.g. as shown) or any other arrangement.Detection elements 402 may operate concurrently or partiallyconcurrently with each other. Specifically, each detection element 402may issue detection information for every sampling duration (e.g. every1 nanosecond). In one example, detector array 400 may be an SiPM(Silicon photomultipliers) which is a solid-statesingle-photon-sensitive device built from an array of single photonavalanche diodes (SPADs, serving as detection elements 402) on a commonsilicon substrate. Similar photomultipliers from other, non-siliconmaterials may also be used. Although an SiPM device works indigital/switching mode, the SiPM is an analog device because all themicrocells are read in parallel, making it possible to generate signalswithin a dynamic range from a single photon to hundreds and thousands ofphotons detected by the different SPADs. As mentioned above, more thanone type of sensor may be implemented (e.g. SiPM and APD). Possibly,sensing unit 106 may include at least one APD integrated into an SiPMarray and/or at least one APD detector located next to an SiPM on aseparate or common silicon substrate.

In one embodiment, detection elements 402 may be grouped into aplurality of regions 404. The regions are geometrical locations orenvironments within sensor 116 (e.g. within detector array 400)—and maybe shaped in different shapes (e.g. rectangular as shown, squares,rings, and so on, or in any other shape). While not all of theindividual detectors, which are included within the geometrical area ofa region 404, necessarily belong to that region, in most cases they willnot belong to other regions 404 covering other areas of the sensor310—unless some overlap is desired in the seams between regions. Asillustrated in FIG. 4A, the regions may be non-overlapping regions 404,but alternatively, they may overlap. Every region may be associated witha regional output circuitry 406 associated with that region. Theregional output circuitry 406 may provide a region output signal of acorresponding group of detection elements 402. For example, the regionof output circuitry 406 may be a summing circuit, but other forms ofcombined output of the individual detector into a unitary output(whether scalar, vector, or any other format) may be employed.Optionally, each region 404 is a single SiPM, but this is notnecessarily so, and a region may be a sub-portion of a single SiPM, agroup of several SiPMs, or even a combination of different types ofdetectors.

In the illustrated example, processing unit 108 is located at aseparated housing 200B (within or outside) host 210 (e.g. within vehicle110), and sensing unit 106 may include a dedicated processor 408 foranalyzing the reflected light. Alternatively, processing unit 108 may beused for analyzing reflected light 206. It is noted that LIDAR system100 may be implemented with multiple housings in other ways than theillustrated example. For example, light deflector 114 may be located ina different housing than projecting unit 102 and/or sensing module 106.In one embodiment, LIDAR system 100 may include multiple housingsconnected to each other in different ways, such as: electric wireconnection, wireless connection (e.g., RF connection), fiber opticscable, and any combination of the above.

In one embodiment, analyzing reflected light 206 may include determininga time of flight for reflected light 206, based on outputs of individualdetectors of different regions. Optionally, processor 408 may beconfigured to determine the time of flight for reflected light 206 basedon the plurality of regions of output signals. In addition to the timeof flight, processing unit 108 may analyze reflected light 206 todetermine the average power across an entire return pulse, and thephoton distribution/signal may be determined over the return pulseperiod (“pulse shape”). In the illustrated example, the outputs of anydetection elements 402 may not be transmitted directly to processor 408,but rather combined (e.g. summed) with signals of other detectors of theregion 404 before being passed to processor 408. However, this is onlyan example and the circuitry of sensor 116 may transmit information froma detection element 402 to processor 408 via other routes (not via aregion output circuitry 406).

FIG. 4B is a diagram illustrating LIDAR system 100 configured to scanthe environment of LIDAR system 100 using a two-dimensional sensor 116.In the example of FIG.

4B, sensor 116 is a matrix of 4×6 detectors 410 (also referred to as“pixels”). In one embodiment, a pixel size may be about lxlmm. Sensor116 is two-dimensional in the sense that it has more than one set (e.g.row, column) of detectors 410 in two non-parallel axes (e.g. orthogonalaxes, as exemplified in the illustrated examples). The number ofdetectors 410 in sensor 116 may vary between differing implementations,e.g. depending on the desired resolution, signal to noise ratio (SNR),desired detection distance, and so on. For example, sensor 116 may haveanywhere between 5 and 5,000 pixels. In another example (not shown inthe figure), sensor 116 may be a one-dimensional matrix (e.g. 1×8pixels).

It is noted that each detector 410 may include a plurality of detectionelements 402, such as Avalanche Photo Diodes (APD), Single PhotonAvalanche Diodes (SPADs), combination of Avalanche Photo Diodes (APD)and Single Photon Avalanche Diodes (SPADs) or detecting elements thatmeasure both the time of flight from a laser pulse transmission event tothe reception event and the intensity of the received photons. Forexample, each detector 410 may include anywhere between 20 and 5,000SPADs. The outputs of detection elements 402 in each detector 410 may besummed, averaged, or otherwise combined to provide a unified pixeloutput.

In the illustrated example, sensing unit 106 may include atwo-dimensional sensor 116 (or a plurality of two-dimensional sensors116), whose field of view is smaller than field of view 120 of LIDARsystem 100. In this discussion, field of view 120 (the overall field ofview which can be scanned by LIDAR system 100 without moving, rotatingor rolling in any direction) is denoted “first FOV 412”, and the smallerFOV of sensor 116 is denoted “second FOV 414” (interchangeably“instantaneous FOV”). The coverage area of second FOV 414 relative tothe first FOV 412 may differ, depending on the specific use of LIDARsystem 100, and may be, for example, between 0.5% and 50%. In oneexample, second FOV 414 may be between about 0.05° and 1° elongated inthe vertical dimension. Even if LIDAR system 100 includes more than onetwo-dimensional sensor 116, the combined field of view of the sensorsarray may still be smaller than the first FOV 412, e.g. by a factor ofat least 5, by a factor of at least 10, by a factor of at least 20, orby a factor of at least 50, for example.

In order to cover first FOV 412, scanning unit 106 may direct photonsarriving from different parts of the environment to sensor 116 atdifferent times. In the illustrated monostatic configuration, togetherwith directing projected light 204 towards field of view 120 and whenleast one light deflector 114 is located in an instantaneous position,scanning unit 106 may also direct reflected light 206 to sensor 116.Typically, at every moment during the scanning of first FOV 412, thelight beam emitted by LIDAR system 100 covers part of the environmentwhich is larger than the second FOV 414 (in angular opening) andincludes the part of the environment from which light is collected byscanning unit 104 and sensor 116.

FIG. 4C is a diagram illustrating an example of a two-dimensional sensor116. In this embodiment, sensor 116 is a matrix of 8×5 detectors 410 andeach detector 410 includes a plurality of detection elements 402. In oneexample, detector 410A is located in the second row (denoted “R2”) andthird column (denoted “C3”) of sensor 116, which includes a matrix of4×3 detection elements 402. In another example, detector 410B located inthe fourth row (denoted “R4”) and sixth column (denoted “C6”) of sensor116 includes a matrix of 3>3 detection elements 402. Accordingly, thenumber of detection elements 402 in each detector 410 may be constant,or may vary, and differing detectors 410 in a common array may have adifferent number of detection elements 402. The outputs of all detectionelements 402 in each detector 410 may be summed, averaged, or otherwisecombined to provide a single pixel-output value. It is noted that whiledetectors 410 in the example of FIG. 4C are arranged in a rectangularmatrix (straight rows and straight columns), other arrangements may alsobe used, e.g. a circular arrangement or a honeycomb arrangement.

According to some embodiments, measurements from each detector 410 mayenable determination of the time of flight from a light pulse emissionevent to the reception event and the intensity of the received photons.The reception event may be the result of the light pulse being reflectedfrom object 208. The time of flight may be a timestamp value thatrepresents the distance of the reflecting object to optional opticalwindow 124. Time of flight values may be realized by photon detectionand counting methods, such as Time Correlated Single Photon Counters(TCSPC), analog methods for photon detection such as signal integrationand qualification (via analog to digital converters or plaincomparators) or otherwise.

In some embodiments and with reference to FIG. 4B, during a scanningcycle, each instantaneous position of at least one light deflector 114may be associated with a particular portion 122 of field of view 120.The design of sensor 116 enables an association between the reflectedlight from a single portion of field of view 120 and multiple detectors410. Therefore, the scanning resolution of LIDAR system may berepresented by the number of instantaneous positions (per scanningcycle) times the number of detectors 410 in sensor 116. The informationfrom each detector 410 (i.e., each pixel) represents the basic dataelement from which the captured field of view in the three-dimensionalspace is built. This may include, for example, the basic element of apoint cloud representation, with a spatial position and an associatedreflected intensity value. In one embodiment, the reflections from asingle portion of field of view 120 that are detected by multipledetectors 410 may be returning from different objects located in thesingle portion of field of view 120. For example, the single portion offield of view 120 may be greater than 50×50 cm at the far field, whichcan easily include two, three, or more objects partly covered by eachother.

FIG. 4D is a cross cut diagram of a part of sensor 116, in accordancewith examples of the presently disclosed subject matter. The illustratedpart of sensor 116 includes a part of a detector array 400 whichincludes four detection elements 402 (e.g., four SPADs, four APDs).Detector array 400 may be a photodetector sensor realized incomplementary metal—oxide— semiconductor (CMOS). Each of the detectionelements 402 has a sensitive area, which is positioned within asubstrate surrounding. While not necessarily so, sensor 116 may be usedin a monostatic LiDAR system having a narrow field of view (e.g.,because scanning unit 104 scans different parts of the field of view atdifferent times). The narrow field of view for the incoming lightbeam—if implemented—eliminates the problem of out-of-focus imaging. Asexemplified in FIG. 4D, sensor 116 may include a plurality of lenses 422(e.g., microlenses), each lens 422 may direct incident light toward adifferent detection element 402 (e.g., toward an active area ofdetection element 402), which may be usable when out-of-focus imaging isnot an issue. Lenses 422 may be used for increasing an optical fillfactor and sensitivity of detector array 400, because most of the lightthat reaches sensor 116 may be deflected toward the active areas ofdetection elements 402

Detector array 400, as exemplified in FIG. 4D, may include severallayers built into the silicon substrate by various methods (e.g.,implant) resulting in a sensitive area, contact elements to the metallayers and isolation elements (e.g., shallow trench implant STI, guardrings, optical trenches, etc.). The sensitive area may be a volumetricelement in the CMOS detector that enables the optical conversion ofincoming photons into a current flow given an adequate voltage bias isapplied to the device. In the case of a APD/SPAD, the sensitive areawould be a combination of an electrical field that pulls electronscreated by photon absorption towards a multiplication area where aphoton induced electron is amplified creating a breakdown avalanche ofmultiplied electrons.

A front side illuminated detector (e.g., as illustrated in FIG. 4D) hasthe input optical port at the same side as the metal layers residing ontop of the semiconductor (Silicon). The metal layers are required torealize the electrical connections of each individual photodetectorelement (e.g., anode and cathode) with various elements such as: biasvoltage, quenching/ballast elements, and other photodetectors in acommon array. The optical port through which the photons impinge uponthe detector sensitive area is comprised of a passage through the metallayer. It is noted that passage of light from some directions throughthis passage may be blocked by one or more metal layers (e.g., metallayer ML6, as illustrated for the leftmost detector elements 402 in FIG.4D). Such blockage reduces the total optical light absorbing efficiencyof the detector.

FIG. 4E illustrates three detection elements 402, each with anassociated lens 422, in accordance with examples of the presentlydisclosed subject matter. Each of the three detection elements of FIG.4E, denoted 402(1), 402(2), and 402(3), illustrates a lens configurationwhich may be implemented in associated with one or more of the detectingelements 402 of sensor 116. It is noted that combinations of these lensconfigurations may also be implemented.

In the lens configuration illustrated with regards to detection element402(1), a focal point of the associated lens 422 may be located abovethe semiconductor surface. Optionally, openings in different metallayers of the detection element may have different sizes aligned withthe cone of focusing light generated by the associated lens 422. Such astructure may improve the signal-to-noise and resolution of the array400 as a whole device. Large metal layers may be important for deliveryof power and ground shielding. This approach may be useful, e.g., with amonostatic LiDAR design with a narrow field of view where the incominglight beam is comprised of parallel rays and the imaging focus does nothave any consequence to the detected signal.

In the lens configuration illustrated with regards to detection element402(2), an efficiency of photon detection by the detection elements 402may be improved by identifying a sweet spot. Specifically, aphotodetector implemented in CMOS may have a sweet spot in the sensitivevolume area where the probability of a photon creating an avalancheeffect is the highest. Therefore, a focal point of lens 422 may bepositioned inside the sensitive volume area at the sweet spot location,as demonstrated by detection elements 402(2). The lens shape anddistance from the focal point may take into account the refractiveindices of all the elements the laser beam is passing along the way fromthe lens to the sensitive sweet spot location buried in thesemiconductor material.

In the lens configuration illustrated with regards to the detectionelement on the right of FIG. 4E, an efficiency of photon absorption inthe semiconductor material may be improved using a diffuser andreflective elements. Specifically, a near IR wavelength requires asignificantly long path of silicon material in order to achieve a highprobability of absorbing a photon that travels through. In a typicallens configuration, a photon may traverse the sensitive area and may notbe absorbed into a detectable electron. A long absorption path thatimproves the probability for a photon to create an electron renders thesize of the sensitive area towards less practical dimensions (tens of umfor example) for a CMOS device fabricated with typical foundryprocesses. The rightmost detector element in FIG. 4E demonstrates atechnique for processing incoming photons. The associated lens 422focuses the incoming light onto a diffuser element 424. In oneembodiment, light sensor 116 may further include a diffuser located inthe gap distant from the outer surface of at least some of thedetectors. For example, diffuser 424 may steer the light beam sideways(e.g., as perpendicular as possible) towards the sensitive area and thereflective optical trenches 426. The diffuser is located at the focalpoint, above the focal point, or below the focal point. In thisembodiment, the incoming light may be focused on a specific locationwhere a diffuser element is located. Optionally, detector element 422 isdesigned to optically avoid the inactive areas where a photon inducedelectron may get lost and reduce the effective detection efficiency.Reflective optical trenches 426 (or other forms of optically reflectivestructures) cause the photons to bounce back and forth across thesensitive area, thus increasing the likelihood of detection. Ideally,the photons will get trapped in a cavity consisting of the sensitivearea and the reflective trenches indefinitely until the photon isabsorbed and creates an electron/hole pair.

Consistent with the present disclosure, a long path is created for theimpinging photons to be absorbed and contribute to a higher probabilityof detection. Optical trenches may also be implemented in detectingelement 422 for reducing cross talk effects of parasitic photons createdduring an avalanche that may leak to other detectors and cause falsedetection events. According to some embodiments, a photo detector arraymay be optimized so that a higher yield of the received signal isutilized, meaning, that as much of the received signal is received andless of the signal is lost to internal degradation of the signal. Thephoto detector array may be improved by: (a) moving the focal point at alocation above the semiconductor surface, optionally by designing themetal layers above the substrate appropriately; (b) steering the focalpoint to the most responsive/sensitive area (or “sweet spot”) of thesubstrate; and (c) adding a diffuser above the substrate to steer thesignal toward the “sweet spot” and/or adding reflective material to thetrenches so that deflected signals are reflected back to the “sweetspot.”

While in some lens configurations, lens 422 may be positioned so thatits focal point is above a center of the corresponding detection element402, it is noted that this is not necessarily so. In other lensconfiguration, a position of the focal point of the lens 422 withrespect to a center of the corresponding detection element 402 isshifted based on a distance of the respective detection element 402 froma center of the detection array 400. This may be useful in relativelylarger detection arrays 400, in which detector elements further from thecenter receive light in angles which are increasingly off-axis. Shiftingthe location of the focal points (e.g., toward the center of detectionarray 400) allows correcting for the incidence angles. Specifically,shifting the location of the focal points (e.g., toward the center ofdetection array 400) allows correcting for the incidence angles whileusing substantially identical lenses 422 for all detection elements,which are positioned at the same angle with respect to a surface of thedetector.

Adding an array of lenses 422 to an array of detection elements 402 maybe useful when using a relatively small sensor 116 which covers only asmall part of the field of view because in such a case, the reflectionsignals from the scene reach the detectors array 400 from substantiallythe same angle, and it is, therefore, easy to focus all the light ontoindividual detectors. It is also noted, that in one embodiment, lenses422 may be used in LIDAR system 100 to prioritize the overallprobability of detection of the entire array 400 (preventing photonsfrom being “wasted” in the dead area between detectors/sub-detectors) atthe expense of spatial distinctiveness. This embodiment is in contrastto prior art implementations such as a CMOS RGB camera, which prioritizespatial distinctiveness (i.e., light that propagates in the direction ofdetection element A is not allowed to be directed by the lens towarddetection element B, that is, to “bleed” to another detection element ofthe array). Optionally, sensor 116 includes an array of lenses 422, eachbeing correlated to a corresponding detection element 402, while atleast one of the lenses 422 deflects light which propagates to a firstdetection element 402 toward a second detection element 402 (thereby itmay increase the overall probability of detection of the entire array).

Specifically, consistent with some embodiments of the presentdisclosure, light sensor 116 may include an array of light detectors(e.g., detector array 400), each light detector (e.g., detector 410)being configured to cause an electric current to flow when light passesthrough an outer surface of a respective detector. In addition, lightsensor 116 may include at least one micro-lens configured to directlight toward the array of light detectors, the at least one micro-lenshaving a focal point. Light sensor 116 may further include at least onelayer of conductive material interposed between the at least onemicro-lens and the array of light detectors and having a gap therein topermit light to pass from the at least one micro-lens to the array, theat least one layer being sized to maintain a space between the at leastone micro-lens and the array to cause the focal plane to be located inthe gap, at a location spaced from the detecting surfaces of the arrayof light detectors.

In related embodiments, each detector may include a plurality of SinglePhoton Avalanche Diodes (SPADs) or a plurality of Avalanche Photo Diodes(APD). The conductive material may be a multi-layer metal constriction,and the at least one layer of conductive material may be electricallyconnected to detectors in the array. In one example, the at least onelayer of conductive material includes a plurality of layers. Inaddition, the gap may be shaped to converge from the at least onemicro-lens toward the focal point, and to diverge from a region of thefocal point toward the array. In other embodiments, light sensor 116 mayfurther include at least one reflector adjacent each photo detector. Inone embodiment, a plurality of micro-lenses may be arranged in a lensarray and the plurality of detectors may be arranged in a detectorarray. In another embodiment, the plurality of micro-lenses may includea single lens configured to project light to a plurality of detectors inthe array.

Referring by way of a nonlimiting example to FIGS. 2E, 2F and 2G, it isnoted that the one or more sensors 116 of system 100 may receive lightfrom a scanning deflector 114 or directly from the FOV without scanning.Even if light from the entire FOV arrives to the at least one sensor 116at the same time, in some implementations the one or more sensors 116may sample only parts of the FOV for detection output at any given time.For example, if the illumination of projection unit 102 illuminatesdifferent parts of the FOV at different times (whether using a deflector114 and/or by activating different light sources 112 at differenttimes), light may arrive at all of the pixels or sensors 116 of sensingunit 106, and only pixels/sensors which are expected to detect the LIDARillumination may be actively collecting data for detection outputs. Thisway, the rest of the pixels/sensors do not unnecessarily collect ambientnoise. Referring to the scanning—in the outbound or in the inbounddirections—it is noted that substantially different scales of scanningmay be implemented. For example, in some implementations the scannedarea may cover 1% or 0.1% of the FOV, while in other implementations thescanned area may cover 10% or 25% of the FOV. All other relativeportions of the FOV values may also be implemented, of course.

The Processing Unit

FIGS. 5A-5C depict different functionalities of processing units 108 inaccordance with some embodiments of the present disclosure.Specifically, FIG. 5A is a diagram illustrating emission patterns in asingle frame-time for a single portion of the field of view, FIG. 5B isa diagram illustrating emission scheme in a single frame-time for thewhole field of view, and. FIG. 5C is a diagram illustrating the actuallight emission projected towards the field of view during a singlescanning cycle.

FIG. 5A illustrates four examples of emission patterns in a singleframe-time for a single portion 122 of field of view 120 associated withan instantaneous position of at least one light deflector 114.Consistent with embodiments of the present disclosure, processing unit108 may control at least one light source 112 and light deflector 114(or coordinate the operation of at least one light source 112 and atleast one light deflector 114) in a manner enabling light flux to varyover a scan of field of view 120. Consistent with other embodiments,processing unit 108 may control only at least one light source 112 andlight deflector 114 may be moved or pivoted in a fixed predefinedpattern.

Diagrams A-D in FIG. 5A depict the power of light emitted towards asingle portion 122 of field of view 120 over time. In Diagram A,processor 118 may control the operation of light source 112 in a mannersuch that during scanning of field of view 120 an initial light emissionis projected toward portion 122 of field of view 120. When projectingunit 102 includes a pulsed-light light source, the initial lightemission may include one or more initial pulses (also referred to as“pilot pulses”). Processing unit 108 may receive from sensor 116 pilotinformation about reflections associated with the initial lightemission. In one embodiment, the pilot information may be represented asa single signal based on the outputs of one or more detectors (e.g. oneor more SPADs, one or more APDs, one or more SiPMs, etc.) or as aplurality of signals based on the outputs of multiple detectors. In oneexample, the pilot information may include analog and/or digitalinformation. In another example, the pilot information may include asingle value and/or a plurality of values (e.g. for different timesand/or parts of the segment).

Based on information about reflections associated with the initial lightemission, processing unit 108 may be configured to determine the type ofsubsequent light emission to be projected towards portion 122 of fieldof view 120. The determined subsequent light emission for the particularportion of field of view 120 may be made during the same scanning cycle(i.e., in the same frame) or in a subsequent scanning cycle (i.e., in asubsequent frame).

In Diagram B, processor 118 may control the operation of light source112 in a manner such that during scanning of field of view 120 lightpulses in different intensities are projected towards a single portion122 of field of view 120. In one embodiment, LIDAR system 100 may beoperable to generate depth maps of one or more different types, such asany one or more of the following types: point cloud model, polygon mesh,depth image (holding depth information for each pixel of an image or ofa 2D array), or any other type of 3D model of a scene. The sequence ofdepth maps may be a temporal sequence, in which different depth maps aregenerated at a different time. Each depth map of the sequence associatedwith a scanning cycle (interchangeably “frame”) may be generated withinthe duration of a corresponding subsequent frame-time. In one example, atypical frame-time may last less than a second. In some embodiments,LIDAR system 100 may have a fixed frame rate (e.g. 10 frames per second,25 frames per second, 50 frames per second) or the frame rate may bedynamic. In other embodiments, the frame-times of different frames maynot be identical across the sequence. For example, LIDAR system 100 mayimplement a 10 frames-per-second rate that includes generating a firstdepth map in 100 milliseconds (the average), a second frame in 92milliseconds, a third frame at 142 milliseconds, and so on.

In Diagram C, processor 118 may control the operation of light source112 in a manner such that during scanning of field of view 120 lightpulses associated with different durations are projected towards asingle portion 122 of field of view 120. In one embodiment, LIDAR system100 may be operable to generate a different number of pulses in eachframe. The number of pulses may vary between 0 to 32 pulses (e.g., 1, 5,12, 28, or more pulses) and may be based on information derived fromprevious emissions. The time between light pulses may depend on desireddetection range and can be between 500 ns and 5000 ns. In one example,processing unit 108 may receive from sensor 116 information aboutreflections associated with each light-pulse. Based on the information(or the lack of information), processing unit 108 may determine ifadditional light pulses are needed. It is noted that the durations ofthe processing times and the emission times in diagrams A-D are notin-scale. Specifically, the processing time may be substantially longerthan the emission time. In diagram D, projecting unit 102 may include acontinuous-wave light source. In one embodiment, the initial lightemission may include a period of time where light is emitted and thesubsequent emission may be a continuation of the initial emission, orthere may be a discontinuity. In one embodiment, the intensity of thecontinuous emission may change over time.

Consistent with some embodiments of the present disclosure, the emissionpattern may be determined per each portion of field of view 120. Inother words, processor 118 may control the emission of light to allowdifferentiation in the illumination of different portions of field ofview 120. In one example, processor 118 may determine the emissionpattern for a single portion 122 of field of view 120, based ondetection of reflected light from the same scanning cycle (e.g., theinitial emission), which makes LIDAR system 100 extremely dynamic. Inanother example, processor 118 may determine the emission pattern for asingle portion 122 of field of view 120, based on detection of reflectedlight from a previous scanning cycle. The differences in the patterns ofthe subsequent emissions may result from determining different valuesfor light-source parameters for the subsequent emission, such as any oneof the following.

-   a. Overall energy of the subsequent emission.-   b. Energy profile of the subsequent emission.-   c. A number of light-pulse-repetition per frame.-   d. Light modulation characteristics such as duration, rate, peak,    average power, and pulse shape.-   e. Wave properties of the subsequent emission, such as polarization,    wavelength, etc.

Consistent with the present disclosure, the differentiation in thesubsequent emissions may be put to different uses. In one example, it ispossible to limit emitted power levels in one portion of field of view120 where safety is a consideration, while emitting higher power levels(thus improving signal-to-noise ratio and detection range) for otherportions of field of view 120. This is relevant for eye safety, but mayalso be relevant for skin safety, safety of optical systems, safety ofsensitive materials, and more. In another example, it is possible todirect more energy towards portions of field of view 120 where it willbe of greater use (e.g. regions of interest, further distanced targets,low reflection targets, etc.) while limiting the lighting energy toother portions of field of view 120 based on detection results from thesame frame or previous frame. It is noted that processing unit 108 mayprocess detected signals from a single instantaneous field of viewseveral times within a single scanning frame time; for example,subsequent emission may be determined after each pulse emission, orafter a number of pulse emissions.

FIG. 5B illustrates three examples of emission schemes in a singleframe-time for field of view 120. Consistent with embodiments of thepresent disclosure, at least one processing unit 108 may use obtainedinformation to dynamically adjust the operational mode of LIDAR system100 and/or determine values of parameters of specific components ofLIDAR system 100. The obtained information may be determined fromprocessing data captured in field of view 120, or received (directly orindirectly) from host 210. Processing unit 108 may use the obtainedinformation to determine a scanning scheme for scanning the differentportions of field of view 120. The obtained information may include acurrent light condition, a current weather condition, a current drivingenvironment of the host vehicle, a current location of the host vehicle,a current trajectory of the host vehicle, a current topography of roadsurrounding the host vehicle, or any other condition or objectdetectable through light reflection. In some embodiments, the determinedscanning scheme may include at least one of the following: (a) adesignation of portions within field of view 120 to be actively scannedas part of a scanning cycle, (b) a projecting plan for projecting unit102 that defines the light emission profile at different portions offield of view 120; (c) a deflecting plan for scanning unit 104 thatdefines, for example, a deflection direction, frequency, and designatingidle elements within a reflector array; and (d) a detection plan forsensing unit 106 that defines the detectors sensitivity or responsivitypattern.

In addition, processing unit 108 may determine the scanning scheme atleast partially by obtaining an identification of at least one region ofinterest within the field of view 120 and at least one region ofnon-interest within the field of view 120. In some embodiments,processing unit 108 may determine the scanning scheme at least partiallyby obtaining an identification of at least one region of high interestwithin the field of view 120 and at least one region of lower-interestwithin the field of view 120. The identification of the at least oneregion of interest within the field of view 120 may be determined, forexample, from processing data captured in field of view 120, based ondata of another sensor (e.g. camera, GPS), received (directly orindirectly) from host 210, or any combination of the above. In someembodiments, the identification of at least one region of interest mayinclude identification of portions, areas, sections, pixels, or objectswithin field of view 120 that are important to monitor. Examples ofareas that may be identified as regions of interest may includecrosswalks, moving objects, people, nearby vehicles or any otherenvironmental condition or object that may be helpful in vehiclenavigation. Examples of areas that may be identified as regions ofnon-interest (or lower-interest) may be static (non-moving) far-awaybuildings, a skyline, an area above the horizon and objects in the fieldof view. Upon obtaining the identification of at least one region ofinterest within the field of view 120, processing unit 108 may determinethe scanning scheme or change an existing scanning scheme. Further todetermining or changing the light-source parameters (as describedabove), processing unit 108 may allocate detector resources based on theidentification of the at least one region of interest. In one example,to reduce noise, processing unit 108 may activate detectors 410 where aregion of interest is expected and disable detectors 410 where regionsof non-interest are expected. In another example, processing unit 108may change the detector sensitivity, e.g., increasing sensor sensitivityfor long range detection where the reflected power is low.

Diagrams A-C in FIG. 5B depict examples of different scanning schemesfor scanning field of view 120. Each square in field of view 120represents a different portion 122 associated with an instantaneousposition of at least one light deflector 114. Legend 500 details thelevel of light flux represented by the filling pattern of the squares.Diagram A depicts a first scanning scheme in which all of the portionshave the same importance/priority and a default light flux is allocatedto them. The first scanning scheme may be utilized in a start-up phaseor periodically interleaved with another scanning scheme to monitor thewhole field of view for unexpected/new objects. In one example, thelight source parameters in the first scanning scheme may be configuredto generate light pulses at constant amplitudes. Diagram B depicts asecond scanning scheme in which a portion of field of view 120 isallocated with high light flux while the rest of field of view 120 isallocated with default light flux and low light flux. The portions offield of view 120 that are the least interesting may be allocated withlow light flux. Diagram C depicts a third scanning scheme in which acompact vehicle and a bus (see silhouettes) are identified in field ofview 120. In this scanning scheme, the edges of the vehicle and bus maybe tracked with high power and the central mass of the vehicle and busmay be allocated with less light flux (or no light flux). Such lightflux allocation enables concentration of more of the optical budget onthe edges of the identified objects and less on their center which haveless importance.

FIG. 5C illustrating the emission of light towards field of view 120during a single scanning cycle. In the depicted example, field of view120 is represented by an 8 X 9 matrix, where each of the 72 cellscorresponds to a separate portion 122 associated with a differentinstantaneous position of at least one light deflector 114. In thisexemplary scanning cycle, each portion includes one or more white dotsthat represent the number of light pulses projected toward that portion,and some portions include black dots that represent reflected light fromthat portion detected by sensor 116. As shown, field of view 120 isdivided into three sectors: sector I on the right side of field of view120, sector II in the middle of field of view 120, and sector III on theleft side of field of view 120. In this exemplary scanning cycle, sectorI was initially allocated with a single light pulse per portion; sectorII, previously identified as a region of interest, was initiallyallocated with three light pulses per portion; and sector III wasinitially allocated with two light pulses per portion. Also as shown,scanning of field of view 120 reveals four objects 208: two free-formobjects in the near field (e.g., between 5 and 50 meters), arounded-square object in the mid field (e.g., between 50 and 150meters), and a triangle object in the far field (e.g., between 150 and500 meters). While the discussion of FIG. 5C uses number of pulses as anexample of light flux allocation, it is noted that light flux allocationto different parts of the field of view may also be implemented in otherways such as: pulse duration, pulse angular dispersion, wavelength,instantaneous power, photon density at different distances from lightsource 112, average power, pulse power intensity, pulse width, pulserepetition rate, pulse sequence, pulse duty cycle, wavelength, phase,polarization, and more. The illustration of the light emission as asingle scanning cycle in FIG. 5C demonstrates different capabilities ofLIDAR system 100. In a first embodiment, processor 118 is configured touse two light pulses to detect a first object (e.g., the rounded-squareobject) at a first distance, and to use three light pulses to detect asecond object (e.g., the triangle object) at a second distance greaterthan the first distance. In a second embodiment, processor 118 isconfigured to allocate more light to portions of the field of view wherea region of interest is identified. Specifically, in the presentexample, sector II was identified as a region of interest andaccordingly it was allocated with three light pulses while the rest offield of view 120 was allocated with two or less light pulses. In athird embodiment, processor 118 is configured to control light source112 in a manner such that only a single light pulse is projected towardto portions B1, B2, and Cl in FIG. 5C, although they are part of sectorIII that was initially allocated with two light pulses per portion. Thisoccurs because the processing unit 108 detected an object in the nearfield based on the first light pulse. Allocation of less than maximalamount of pulses may also be a result of other considerations. Forexample, in at least some regions, detection of object at a firstdistance (e.g. a near field object) may result in reducing an overallamount of light emitted to this portion of field of view 120.

Additional details and examples on different components of LIDAR system100 and their associated functionalities are included in Applicant'sU.S. patent application Ser. No. 15/391,916 filed Dec. 28, 2016;Applicant's U.S. patent application Ser. No. 15/393,749 filed Dec. 29,2016; Applicant's U.S. patent application Ser. No. 15/393,285 filed Dec.29, 2016; and Applicant's U.S. patent application Ser. No. 15/393,593filed Dec. 29, 2016, which are incorporated herein by reference in theirentirety.

Example Implementation: Vehicle

FIGS. 6A-6C illustrate the implementation of LIDAR system 100 in avehicle (e.g., vehicle 110). Any of the aspects of LIDAR system 100described above or below may be incorporated into vehicle 110 to providea range-sensing vehicle. Specifically, in this example, LIDAR system 100integrates multiple scanning units 104 and potentially multipleprojecting units 102 in a single vehicle. In one embodiment, a vehiclemay take advantage of such a LIDAR system to improve power, range andaccuracy in the overlap zone and beyond it, as well as redundancy insensitive parts of the FOV (e.g. the forward movement direction of thevehicle). As shown in FIG. 6A, vehicle 110 may include a first processor118A for controlling the scanning of field of view 120A, a secondprocessor 118B for controlling the scanning of field of view 120B, and athird processor 118C for controlling synchronization of scanning the twofields of view. In one example, processor 118C may be the vehiclecontroller and may have a shared interface between first processor 118Aand second processor 118B. The shared interface may enable an exchangingof data at intermediate processing levels and a synchronization ofscanning of the combined field of view in order to form an overlap inthe temporal and/or spatial space. In one embodiment, the data exchangedusing the shared interface may be: (a) time of flight of receivedsignals associated with pixels in the overlapped field of view and/or inits vicinity; (b) laser steering position status; (c) detection statusof objects in the field of view.

FIG. 6B illustrates overlap region 600 between field of view 120A andfield of view 120B. In the depicted example, the overlap region isassociated with 24 portions 122 from field of view 120A and 24 portions122 from field of view 120B. Given that the overlap region is definedand known by processors 118A and 118B, each processor may be designed tolimit the amount of light emitted in overlap region 600 in order toconform with an eye safety limit that spans multiple source lights, orfor other reasons such as maintaining an optical budget. In addition,processors 118A and 118B may avoid interferences between the lightemitted by the two light sources by loose synchronization between thescanning unit 104A and scanning unit 104B, and/or by control of thelaser transmission timing, and/or the detection circuit enabling timing.

FIG. 6C illustrates how overlap region 600 between field of view 120Aand field of view 120B may be used to increase the detection distance ofvehicle 110. Consistent with the present disclosure, two or more lightsources 112 projecting their nominal light emission into the overlapzone may be leveraged to increase the effective detection range. Theterm “detection range” may include an approximate distance from vehicle110 at which LIDAR system 100 can clearly detect an object. In oneembodiment, the maximum detection range of LIDAR system 100 is about 300meters, about 400 meters, or about 500 meters. For example, for adetection range of 200 meters, LIDAR system 100 may detect an objectlocated 200 meters (or less) from vehicle 110 at more than 95%, morethan 99%, more than 99.5% of the times, even when the object'sreflectivity may be less than 50% (e.g., less than 20%, less than 10%,or less than 5%).

In addition, LIDAR system 100 may have less than 1% false alarm rate. Inone embodiment, light projected from two light sources that arecollocated in the temporal and spatial space can be utilized to improveSNR and therefore increase the range and/or quality of service for anobject located in the overlap region. Processor 118C may extracthigh-level information from the reflected light in field of view 120Aand 120B. The term “extracting information” may include any process bywhich information associated with objects, individuals, locations,events, etc., is identified in the captured image data by any meansknown to those of ordinary skill in the art. In addition, processors118A and 118B may share the high-level information, such as objects(road delimiters, background, pedestrians, vehicles, etc.), and motionvectors, to enable each processor to become alert to the peripheralregions about to become regions of interest. For example, a movingobject in field of view 120A may be determined to soon be entering fieldof view 120B.

Example Implementation: Surveillance System

FIG. 6D illustrates the implementation of LIDAR system 100 in asurveillance system. As mentioned above, LIDAR system 100 may be fixedto a stationary object 650 that may include a motor or other mechanismsfor rotating the housing of the LIDAR system 100 to obtain a wider fieldof view. Alternatively, the surveillance system may include a pluralityof LIDAR units. In the example depicted in FIG. 6D, the surveillancesystem may use a single rotatable LIDAR system 100 to obtain 3D datarepresenting field of view 120 and to process the 3D data to detectpeople 652, vehicles 654, changes in the environment, or any other formof security-significant data.

Consistent with some embodiment of the present disclosure, the 3D datamay be analyzed to monitor retail business processes. In one embodiment,the 3D data may be used in retail business processes involving physicalsecurity (e.g., detection of: an intrusion within a retail facility, anact of vandalism within or around a retail facility, unauthorized accessto a secure area, and suspicious behavior around cars in a parking lot).In another embodiment, the 3D data may be used in public safety (e.g.,detection of: people slipping and falling on store property, a dangerousliquid spill or obstruction on a store floor, an assault or abduction ina store parking lot, an obstruction of a fire exit, and crowding in astore area or outside of the store). In another embodiment, the 3D datamay be used for business intelligence data gathering (e.g., tracking ofpeople through store areas to determine, for example, how many people gothrough, where they dwell, how long they dwell, how their shoppinghabits compare to their purchasing habits).

Consistent with other embodiments of the present disclosure, the 3D datamay be analyzed and used for traffic enforcement. Specifically, the 3Ddata may be used to identify vehicles traveling over the legal speedlimit or some other road legal requirement. In one example, LIDAR system100 may be used to detect vehicles that cross a stop line or designatedstopping place while a red traffic light is showing. In another example,LIDAR system 100 may be used to identify vehicles traveling in lanesreserved for public transportation. In yet another example, LIDAR system100 may be used to identify vehicles turning in intersections wherespecific turns are prohibited on red.

It should be noted that while examples of various disclosed embodimentshave been described above and below with respect to a control unit thatcontrols scanning of a deflector, the various features of the disclosedembodiments are not limited to such systems. Rather, the techniques forallocating light to various portions of a LIDAR FOV may be applicable toany type of light-based sensing system (LIDAR or otherwise) in whichthere may be a desire or need to direct different amounts of light todifferent portions of the field of view. In some cases, such lightallocation techniques may positively impact detection capabilities, asdescribed herein, but other advantages may also result.

It should also be noted that various sections of the disclosure and theclaims may refer to various components or portions of components (e.g.,light sources, sensors, sensor pixels, field of view portions, field ofview pixels, etc.) using such terms as “first,” “second,” “third,” etc.These terms are used only to facilitate the description of the variousdisclosed embodiments and are not intended to be limiting or to indicateany necessary correlation with similarly named elements or components inother embodiments. For example, characteristics described as associatedwith a “first sensor” in one described embodiment in one section of thedisclosure may or may not be associated with a “first sensor” of adifferent embodiment described in a different section of the disclosure.

It is noted that LIDAR system 100, or any of its components, may be usedtogether with any of the particular embodiments and methods disclosedbelow. Nevertheless, the particular embodiments and methods disclosedbelow are not necessarily limited to LIDAR system 100, and may possiblybe implemented in or by other systems (such as but not limited to otherLIDAR systems, other electrooptical systems, other optical systems,etc.—whichever is applicable). Also, while system 100 is describedrelative to an exemplary vehicle-based LIDAR platform, system 100, anyof its components, and any of the processes described herein may beapplicable to LIDAR systems disposed on other platform types. Likewise,the embodiments and processes disclosed below may be implemented on orby LIDAR systems (or other systems such as other elecrooptical systemsetc.) which are installed on systems disposed on platforms other thanvehicles, or even regardless of any specific platform.

Integratory LIDAR systems

FIGS. 7A through 7E illustrate examples of distributed LIDAR systems 900deployed across different environments, in accordance with examples ofthe presently disclosed subject matter. The LIDAR systems 900 of FIGS.7A through 7E include a plurality of anchored LIDAR sensing units(denoted 101 in these figures) deployed in different locations in theenvironment. The anchored LIDAR sensing units are anchored in the sensethat they are not connected to a vehicle, but are rather connected tothe ground, either directly or via a supporting structure. It is notedthat such an anchored LIDAR sensing unit may be stationary with respectto the ground and/or to the supporting structure, but this is notnecessarily so. For example, an anchored LIDAR sensing unit may pivotabout one or more axes (e.g. in order to detect differing fields ofview, for example pivoting similarly to a surveillance camera), may moveor be moved within a limited distance from an anchoring location, and soon. The supporting structure on which an anchored LIDAR sensing unit isanchored (if any) may be fixed, flexible, moving, etc. For example, thesupporting structure may include a crane arm designed to move theanchored sensing unit in different directions above a road crossing. Ananchored LIDAR sensing unit may be positioned on a pole, a tower, etc.,but this is not necessarily so. An anchored LIDAR sensing unit may be aLIDAR system 100, or any other type of LIDAR system (e.g. scanning ornon-scanning, pulsed light or continuous wave, rotating or non-rotating,etc.). FIG. 7A illustrates anchored LIDAR sensing units mounted on theground (denoted 101B), mounted on poles and on a tower (denoted 101C).Any other supporting structures may also be used (e.g., a building, awall, a rail, a traffic light, a crane, an anchored hot-air balloon).While not necessarily so, two or more of the plurality of anchored LIDARsensing units are mounted at a height of at least 3 meters above groundlevel. Higher heights may also be required. For example, while notnecessarily so, two or more of the plurality of anchored LIDAR sensingunits are mounted at a height of at least 6 meters, 10 meters, 15meters, or 20 meters above ground level, etc. Any two or more of theplurality of anchored LIDAR sensing units may have non-overlapping FOVs,partly overlapping FOVs or substantially overlapping FOVs (e.g., seenfrom different directions).

Each anchored LIDAR sensing unit of the distributed LIDAR systemincludes at least a detector (as exemplified for example with respect toLIDAR system 100) and a communication unit (not illustrated), which mayoptionally be included in one or more housings. Each of the one or moreLIDAR detectors included in such an anchored LIDAR sensing unit 101 maybe configured to detect light signals arriving from objects in a fieldof view of the anchored LIDAR sensing unit, and the communication unitof the anchored LIDAR sensing unit is configured to output detectioninformation which is based on outputs of the at least one detector andwhich is indicative of existence of the objects. An anchored LIDARsensing unit may include a processor, configured to process the lightsignals to determine existence of objects in the field of view of theLIDAR sensing unit. For example, the processor may determine a distanceto different targets in the FOV, the processor may create a point cloudof the FOV (or part of it), and so on. The processor of the anchoredLIDAR sensing unit may be included in the same housing as the detector,but this is not necessarily so.

The communication unit of the LIDAR sensing unit may transmit rawdetection data and/or processed detection data in varying degrees ofprocessing (e.g., point cloud, object detection, detected velocities ofobjects, time stamps, dead areas in which objects may be hidden from thesystem). The communication unit may also be used for transmission ofother types of data, such as operational parameters of the LIDAR sensingunit, and data from additional sensors (e.g., temperature sensor,camera, humidity sensor). The communication unit of the LIDAR sensingunit may also be used for receiving data from the integratory processingunit 103, from other LIDAR sensing units, from other sensors, fromvehicles, or from any other system. Some non-limiting examples ofincoming data which may be received by a LIDAR sensing unit 101 mayinclude instructions (e.g. by integratory processing units), requests(e.g., from vehicles in its vicinity or from neighboring units 101),indications of objects entering the FOV based on data collected by otherLIDAR sensing unit or other sensors, and so on. The communication unitof each of the plurality of LIDAR sensing units may support wired and/orwireless communication with external systems.

In addition to the plurality of anchored LIDAR sensing units 101,distributed LIDAR systems 900 (e.g., such as the one exemplified inFIGS. 7A through 7E) also include one or more integratory processingunits 103, each being configured to receive the detection informationfrom two or more of the plurality of anchored LIDAR sensing units 101,to process the received detection information to provide a threedimensional (3D) model of a scene which is larger than any of the fieldsof view of the independent anchored LIDAR sensing units. The 3D model isbased on information of two or more of the anchored LIDAR sensing units,and therefore includes location information obtained from differentlocations (and therefore, possibly, from different angles).

An integratory processing unit 103 may use data from other types ofsensors as well—in addition to LIDAR data—in the creation of the 3Dmodel. For example, an integratory processing unit may be configured tofurther receive detection information from at least one additionalanchored sensor which includes at least one of the following: a camera,a RADAR, and an ultrasound detector; to process detection information ofthe at least one additional anchored sensor together with the receiveddetection information to provide the 3D model of a part of theenvironment which is larger than any of the field of views of theindependent anchored LIDAR sensing units. In addition to usinginformation of anchored sensor, an integratory processing unit 103 mayalso use information from a movable sensors (e.g., vehicle mountedsensors of one or more vehicles in the environment; a sensor mounted onan aircraft above the scene)—LIDAR and/or other types of sensors.

Integratory processing unit 103 may be a regional processing unit in thesense that it may receive data from LIDAR sensing units (and possiblyadditional types of sensors) located in a certain geographic region(e.g., a 1 km by 1 km area; along a 2 km road). Processing informationfrom geographically proximate group of sensors is useful both in thespeed of communication, and in the generation of a unified/continuous 3Dmodel. In such an implementation, a plurality of regional processingunits may communicate with one another and/or with a higher levelintegration system.

The distributed LIDAR system may further include a regionalcommunication unit configured to obtain at least a part of the 3D modeland to wirelessly transmit 3D data indicative of at least a portion ofthe 3D model to a vehicle 105 (e.g., a car, a truck, a motorcycle, atrain, a combined harvester). In addition—or instead—such a regionalcommunication unit may transfer that 3D data to another type of systemsuch as cellular phone, tablet, etc. The regional communication unit maybe implemented in the same housing as the regional processing unitand/or the integratory processing unit (if not the same), but this isnot necessarily so.

The receiving system (whether a vehicle or not) may be included in thescene (e.g., seen by one or more of the plurality of anchored LIDARsensing units 101), but this is not necessarily so. The receiving system(whether a vehicle or not) may be included and represented in the 3Dmodel (e.g., generated from the data collected by one or more of theplurality of anchored LIDAR sensing units 101), but this is notnecessarily so. The receiving system (whether a vehicle or not) may bemoving in the direction of the scene, but this is not necessarily so. Insuch case, the scene represented in the 3D model may be visible to thereceiving system, but optionally the distributed LIDAR system mayprovide to the receiving system (e.g., vehicle) information which is notvisible to it (e.g., beyond a curve or a hill, beyond a truck or anotherobstacle, etc.).

Integratory processing unit 103 may be an anchored to a stationaryobject (e.g. a building, a pole). Integratory processing unit 103 may bean anchored to a moving object, such as a vehicle (e.g., an aircraft, aleading vehicle of a platoon). The communication between any two or moreunits in the distributed LIDAR system (and auxiliary recipients of 3Ddata) may be wired, wireless, or any combination thereof.

It is noted that the distributed LIDAR system may include one or moreprocessors which are configured to determine operational parameters forat least one of the plurality of anchored LIDAR sensing units 101 basedon detection information of an at least one other sensor (e.g., LIDAR,camera, RADAR, ultrasonic sensor, etc.). For example, the number ofpulses, a region of interest, an illumination level, a scanning rate andso on of an anchored LIDAR system 101 may be determined based oninformation of another detector (e.g., of another anchored LIDAR sensingunit, of camera). For example, if one anchored LIDAR sensing unit 101detects a vehicle in a known location and moving at a detected velocity,the operational parameters of another sensing unit 101 may be modifiedto detect it when it moves between the FOVs of the respective anchoredLIDAR systems.

According to a disclosed embodiment, an integratory LIDAR system mayinclude at least (e.g., as part of a single integratory processing unit103): (a) a communication module for receiving detection informationfrom a plurality of anchored LIDAR sensing units; and (b) a processorconfigured to process the detection information received from theplurality of anchored LIDAR sensing unit to provide a three dimensional(3D) model of a scene which is larger than any of the fields of view ofthe independent anchored LIDAR sensing units. Additional details withrespect to optional implementations of integratory processing unit 103are discussed below with respect to FIGS. 8 and 9 .

While not necessarily so, a distributed LIDAR system may be used forgeofenced areas. For example, a distributed LIDAR system 900 asdiscussed above may be implemented in areas such as:

-   i. A highway section,-   ii. Railway,-   iii. Airport,-   iv. Shuttled campus,-   v. Parking lots,-   vi. Larger areas, such as cities, states or any continuous drivable    land.

A distributed LIDAR system 900 may include:

-   i. Multiple (N) LiDARs (e.g., LIDARs 101) statically positioned in    accordance with LiDARs performance (e.g. range), topography,    expected traffic (e.g. volume, speed), etc.-   ii. Multiple (M) processing units, each having access to    multiple (n) LiDARs data with a possible overlap of LiDARs to    processing unit allocation.-   iii. A bi-directional communication system between processing units.-   iv. A unidirectional (broadcast) or bidirectional communication    system between processing units and vehicles.

Each processing unit (e.g., processing unit 103) may receive LIDAR data(e.g., raw point cloud and/or pre-processed data generated by theanchored LIDAR systems, such as classified objects data), process thedata for scene understanding (e.g. objects and obstacle identification,classification and tracking, drivable areas, localization) and willtransmit this information to the vehicles.

Some advantages of the proposed distributed LIDAR systems are (wheresome of the advantages are applicable to some of the variations whileothers are applicable to all variations):

-   i. In many applications (e.g,. a geofenced area with many moving    vehicles), it may require fewer LiDAR units. For example: US roads    include over 6 million kilometers of road. There are more than 250    million passenger vehicles in the US (and many other vehicles, such    as trucks and other service vehicles). In such an example, a    distributed LIDAR system with over 35 LIDAR sensing units 101 per    kilometer would still be more efficient than having only a single    LiDAR per vehicle. It is noted that higher level of automotive    automation may use more than one LIDAR unit per vehicle.-   ii. The individual anchored LIDAR systems are subject to much more    relaxed requirements for the LiDARs: range, vibration resilience,    power, heat dissipation, size, and so on.-   iii. Superior performance due to one or more of the following:    overlap in the FOVs of differing anchored LIDAR sensing units, fewer    blocked/hidden parts of the scene, LiDARs position at height (better    angle of incidence), ability to detect objects further and behind    corners and walls.-   iv. Better processing capabilities e.g., if each processing unit    receives data from multiple LIDAR sensing units and information from    other processing units. No power and heat dissipation limitations on    processing units.-   v. Fewer or no eye safety issues (e.g., if LIDAR units are placed on    poles and thus at a significant distance from any human eye during    operation of the system).-   vi. Fewer or no blinding by sun or other ambient light source.    Orientation of the fixedly anchored LIDAR units FOVs may be directed    by design toward the ground and/or in accordance with sun locations    in the sky and/or locations and orientation of other ambient light    sources (whether fixed like a building or transitory like vehicles    on roads).-   vii. Lesser effect of rain and/or raindrops on quality of LIDAR    point cloud. Orientation of the fixedly anchored LIDAR units FOVs    may be directed by design toward the ground and/or in accordance    with local wind regimes.-   viii. Improved quality of detection signals processing. Processing    is much easier when compared to vehicle-mounted moving LIDARs:    background map is fixed, easy to detect new objects or other changes    with respect to static background, and distances to background in    each direction of the FOV are known (so no need to look for objects    in a distance greater than the static background, such as below the    ground or behind buildings).-   ix. LIDARs with lower performances may optionally be used, when    compared to vehicle-mounted moving LIDARs. For example, if a fast    going car needs to detect objects in distances of 200 meters ahead    of it, the detection may be achieved by the integrated LIDAR system    using LIDARs of lower detection range (e.g., LIDARs of detection    range of 50 m, mounted every 50 m).

Referring to some of the advantages discussed above which allowutilizing a LIDAR sensing unit with relatively relaxed requirements(e.g., on power consumption, sensitivity to vibration, on size, on cost,on detection range etc.), it is noted that distributed LIDAR system 900allows vehicles to achieve autonomous driving using non-automotive gradeLIDAR systems.

As mentioned above, the at least one integratory processing unit 103 mayoptionally be configured to wirelessly transmit 3D data to vehicles(e.g., as exemplified in FIG. 7A between unit 103 and vehicle 105 in theshape of a lightning bolt). Optionally, the at least one integratoryprocessing unit 103 may provide different kinds of 3D data to differentvehicles. This may be done, for example, based on the type of thevehicle, based on requests of the vehicle, based on a detected speed ofthe vehicle, based on a location of the vehicle with respect to theroad/topography, and so on. For example, an integratory processing unit103 may provide to a slow moving car detailed 3D data in range of 50 mahead of the car and only bounding boxes of detected objects on the roadin larger distances, while at the same time providing to a fast fulltrailer truck detailed distance in range of 400 m ahead of the truck. Inanother example, if a car indicates that it intends to turn right at ajunction, the integratory processing unit 103 may decide to provide tothe car detailed 3D data on the selected right turning road, whileproviding only rudimentary data on this part of the scene to cars whichcontinue on the highway. Optionally, one or more integratory processingunits 103 may be configured (together or separately) to:

i. wirelessly transmit to a first vehicle, based on a first requestreceived from the first vehicle, first 3D data pertaining to a spatialarea at a first time, and to ii. wirelessly transmit to a secondvehicle, based on a second request received from the second vehicle,second 3D data pertaining to the spatial area at the first time, whereinthe first 3D data and the second 3D data comprise 3D data in differentlevels of details.

As mentioned above, the FOVs of the different anchored LIDAR sensingunits may be overlapping or non-overlapping. Different variation ofoverlapping (or lack thereof) are provided in FIGS. 7A through 7E. Alsothe distance between neighboring LIDAR units 101 as well as the overallsize of the area covered by the plurality of anchored LIDAR sensing unis101 may also change. Optionally, a distance between a first anchoredLIDAR sensing unit 101 of the plurality of anchored LIDAR sensing unitsand a second anchored LIDAR sensing unit 101 of the plurality ofanchored LIDAR sensing units exceeds a first detection range of thefirst anchored LIDAR sensing unit and a second detection range of thesecond anchored LIDAR sensing unit. The detection ranges are exemplifiedin some of the diagrams as the FOV of the respective LIDAR sensing unit101.

The one or more integratory processing units 103 may be located indifferent distances from one another (if applicable) and from the LIDARsensing units 101 in different implementations of the disclosedembodiments. The communication between the different units may be wiredor wireless (e.g., as illustrated in FIG. 7C). Optionally, a distancebetween a first anchored LIDAR sensing unit of the plurality of anchoredLIDAR sensing units and at least one integratory processing unit exceedsa first detection range of the first anchored LIDAR sensing unit. Forexample, e.g., as illustrated in FIG. 7A, one or more of the integratoryprocessing units 103 may be positioned away from the scene (e.g., at acontrol center at a nearby city, which could be tens or hundreds ofkilometers away, if not more). While not illustrated, it is noted thatthe anchored LIDAR sensing units 101 may optionally communicate directlywith one another, without the mediation and/or intervention ofintegratory processing unit 103. For example, neighboring anchored LIDARsensing units 101 may transmit to one another detection data,synchronization requests, status reports, and so on. Synchronizationbetween LIDAR units 101 may be achieved, for example, by determining thepulse emission timings of one or more of the LIDAR sensing units 101.Optionally, distributed LIDAR system may include one or moresynchronization controller which is configured to instruct a firstanchored LIDAR sensing unit of the plurality of anchored LIDAR sensingunits to modify its light emission scheme so as to prevent interferencesby the first anchored LIDAR sensing unit to a second anchored LIDARsensing unit of the plurality of anchored LIDAR. The one or moresynchronization controllers may be implemented, for example, as part ofan integratory processing units 103, as part of an anchored LIDARsensing unit 101, or as a stand-alone system. It is noted thatsynchronization between anchored LIDAR sensing units 101 may havedifferent requirements than synchronization between movingvehicle-mounted LIDAR systems, because the geometrical relationships aremuch more constrained.

Referring to FIGS. 7C and 7E, it is noted that in some scenarios, thesame land area needs to be covered by LIDAR sensing units 101 whose FOVsare oriented at opposing (or at least sufficiently different than) eachother. For example, the road in FIGS. 7C and 7E is a two-way road, butthe LIDAR sensing units 101 of FIG. 7C can only provide depth datadetected eastbound. Such data may be insufficient for westbound cars, sothat installation of LIDARs with westbound FOVs may be required. In theexample of FIG. 7E, an eastbound vehicle may receive 3D data which isbased on detection of only eastbound directed LIDAR units 101, or ofboth eastbound and westbound LIDAR units 101. Optionally, one or moreintegratory processing units 103 may be configured to:

i. receive from multiple anchored LIDAR sensing units of the pluralityof anchored LIDAR sensing units detection information pertaining to acommon spatial area included in the fields of view of the multipleanchored LIDAR sensing units;

ii. process the received detection information to provide a 3D model ofthe common spatial area which includes 3D information of opposing sidesof an object in the common spatial area, wherein none of the multipleanchored LIDAR sensing units detects all of the opposing sides.

Referring to distributed LIDAR system 900 as a whole, different types ofanchored LIDAR sensing units 101 may be used in the same system (e.g.,solid state LIDARs, spinning LIDARs, pulsed LIDARs, flash LIDARs, and soon). This may be used, for example, for handling different geographicaland/or topological differences in different parts of the surveilledroads, for handling different traffic characterizations in differentparts of the surveilled roads, and so on. Also, LIDAR sensing units 101of the same kind and/or of different kinds may be operated in differentoperational conditions (e.g., Frame rate, resolution, illuminationpower, and so on). Also, the position of the anchored LIDAR sensingunits 101 with respect to the road may also vary between differentsystems 900 as well as within a single system 900. For example, someLIDAR systems may be positioned above the road, while others may bepositioned on a side of the road. Examples of a distributed LIDARsystems 900 which include anchored LIDAR sensing units 101 of differenttypes are provided in FIGS. 7A and 7D. Optionally, LIDAR systems withSynchronizing parameters between different LIDAR units to get uniformityon the system level.

Notably, system 900 is not necessarily limited only to LIDARs, and othertypes of sensors may be integrated into the system (and provide theirdetection data to the one or more integratory processing units 103).Such additional sensors may optionally be anchored together withanchored LIDAR sensing units 101 (e.g., on the same pole, on the samebuilding). Optionally, an anchored sensing unit may include both a LIDARand one or more other sensors (e.g., camera), possibly in the samehousing and/or sharing other components (e.g., lens, power source,communication module). Some examples of 3D data which may be provided tovehicles 105 or to other systems include, point cloud, bounding boxes,map (including parsed one, e.g., drivable area, lanes, etc.), and othertypes of processed data or raw data. The provided data may also includedata from the other sensors (e.g., camera, radar) which may beintegrated with the LIDAR data or separate therefrom.

The communication between the integratory processing unit 103 to thevehicles may also be used for controlling vehicles in the surveilledscene. For example, the at least one integratory processing unit 103 maybe configured to instruct a driving decision of a vehicle in the scenebased on the 3D model. System 900 may be used for fully controllingvehicles from outside the vehicles (e.g., in confined scenarios likeairport technical vehicles). System 900 may also be used in more limitedcases where most of the driving is done by the vehicles. For example,integratory processing unit 103 may instruct vehicles to brake duringemergencies, to move away from a blocked lane, etc., but leave theroutine driving decisions to each vehicle.

FIG. 8 is a flow chart illustrating method 500 for an integratoryprocessing unit in a distributed LIDAR system, in accordance withexamples of the presently disclosed subject matter. Referring to theexamples set forth with respect to the previous drawings, method 500 maybe implemented by one or more of the at least one integratory processingunit 103 of system 900. It is noted that method 500 includes stages 510,520, 530 and 540. Other stages are optional. For simplicity ofdisclosure, many optional stages were included in a single diagram.However, it is noted that any combination of the various stages ofmethod 500 discussed below may be implemented. Furthermore, the order ofstages 530, 540, 550, and 560 may vary, and any viable order of two ormore of these stages may be executed. It is noted that the discussion ofintegratory processing unit 103 and of distributed LIDAR system 900above is applicable also to method 500, and that any operation andcapability discussed above with respect to integratory processing unit103 may also be incorporated as a stage of method 500, mutatis mutandis.

Stage 510 includes receiving detection information from a plurality ofanchored LIDAR sensing units, each covering a different field of view.Optionally, method 500 may also include stage 511 of receiving detectioninformation from at least one other anchored sensing unit (e.g., camera,RADAR) covering an area which is detected by at least one of theplurality of anchored LIDAR sensing units. Referring to the example setforth with respect to FIG. 9 below, stage 510 may be implemented by acommunication module of system 103 (e.g., reception communication module210). Dedicated software or firmware interfaces may be used for theprocessing of different kinds of incoming communications. For example,detection data interface 221 may be used for handing incoming detectiondata from anchored LIDAR sensing units 101, from other types of anchoredsensing units, and so on. It is further noted that detection data (e.g.,LIDAR data) may also be received from vehicle-mounted sensors onvehicles and integrated into the 3D model generated by system 103. Otherdata from anchored sensing units may be handled by sensing unitmanagement interface 222, e.g., requests for synchronization with otherLIDAR units, status reports, and so on. Requests and information fromvehicles and other recipients of the 3D model may be handled by clientsmanagement interface 223.

Stage 520 includes processing the received detection information toprovide a 3D model of a scene which is larger than any of the fields ofview of the independent anchored LIDAR sensing units. The processing ofstage 520 may include any one or more of stages 521, 522, 523, 524 and525. Referring to the example set forth with respect to the FIG. 9below, stage 520 may be implemented by 3D data processor 230.

Stage 521 includes combining 3D data points from different LIDAR sensingunits into a unified 3D model. Stage 522 includes cleaning the 3D modelfrom noises, duplications, etc. Stage 523 includes identifying andclassifying objects in the 3D model. Stage 524 includes identifying anobject based on 3D data points from different LIDAR sensing units. It isnoted that some objects may not be detected or classified using datapoints from only one anchored LIDAR system, but using data pointscollected by several LIDAR sensing units may enable the identificationor classification of such objects. Optionally, stage 520 may include andmay be based in part on the outputs of optional stage 525 which includesprocessing and integrating detection information of the other sensors.Referring to the example set forth with respect to the FIG. 9 below,stage 521 and 522 may be implemented by 3D model integration module 231,and stages 523 and 524 may be implemented by object detection module 232and 3D object classifier 233.

Stage 530 of method 500 includes preparing different 3D data to send todifferent recipients. As mentioned above, the preparation of the datamay be based on many factors, such as requests by clients, by kinematicparameters or other parameters of the clients, and so on. Stage 530 mayinclude optional stage 531 of receiving requests from vehicles and/orother clients. Stage 530 may include optional stage 532 of processingthe 3D model to determine a location, kinematic parameters and/or otherparameters of recipient vehicles. Referring to the example set forthwith respect to the FIG. 9 below, stage 530 may be implemented by 3Ddata processor 230.

Stage 540 includes sending different 3D data of the scene to differentrecipients, whether recipients which are located within the scene (e.g.,vehicles, pedestrians, businesses) or other recipients (e.g., municipalauthorities). Stage 540 may include sending to a vehicle which is not inthe FOV of a first anchored LIDAR sensing unit 3D data of that firstLIDAR unit, based on detection of the vehicle by another anchored LIDARsensing unit. For example, unit 103 may detect a vehicle in a part ofthe road detected by a first LIDAR, determine that its kinematicparameters require to provide the vehicle 3D data collected by anotherLIDAR system 300 meters away, and preparing that data to send to thevehicle. Referring to the example set forth with respect to FIG. 9below, stage 540 may be implemented by 3D data processor 230.

Stage 550 includes sending instructions to at least one of the anchoredLIDAR sensing units. The instruction may include, for example,operational parameters, FOV parameters, and so on. Such instructions mayalso include synchronization instructions, for improving the overallperformance of detection in the system, by reducing inter-LIDARinterferences. Referring to the example set forth with respect to FIG. 9below, stage 550 may be implemented by sensing unit controller 240.

Stage 560 includes controlling driving of vehicles in the scene.Referring to the example set forth with respect to FIG. 9 below, stage560 may be implemented by traffic control module 250. Drivinginstructions may include direct instructions (e.g., steeringinstruction, braking and accelerating instructions), and may alsoinclude more general instructions (e.g., which lanes are permitted fordriving, drivable area, maximum speed). Referring to the example setforth with respect to FIG. 9 below, stages 540, 550 and 560 may befacilitated by a communication unit of system 103, such as outgoing (Tx)communication module 260.

FIG. 9 is a block diagram of integratory processing unit 103, inaccordance with examples of the presently disclosed subject matter. Thefunctionality of the different components is described with respect todifferent stages of method 500. Additional component may also beimplemented, such as power source 290, tangible memory storage 280,operating system 270, and so on.

Geo-Specific LIDAR Detection Patterns

In distributed LIDAR system 900, different LIDARs sensing units may beoperated with using different definition and requirements. Therefore,identical LIDAR sensing units (e.g., LIDAR systems 100) may be operatedwith different conditions, such as FOV, resolution, frame-rate, etc.Optionally, integratory processing unit 103 may be operable to determinedifferent operational parameters (such as resolution, FOV, detectionrange, frame-rate, susceptibility to noise, eye-safety requirements, andso on) for different anchored LIDAR sensing units 101 from which itreceives information, based on any combination of one or more of thefollowing of the non-limiting list:

-   i. Topography of the FOV detectable by the LIDAR sensing unit.-   ii. Geometrical considerations, such as height and orientation of    the LIDAR sensing unit with respect to fixed objects in the scene,    interferences and blocking objects (e.g., trees, buildings).-   iii. Classification of the scene part detectable by the LIDAR (e.g.,    drivable area, roadsides, junctions, crosswalks).-   iv. Requirements of vehicles or other recipients, such as required    resolution, frame rate, detection range.-   v. Weather and other visibility affecting conditions.-   vi. Detection results received and analyzed in the past (e.g., in    the last frame, minute, hour, day).-   vii. Traffic data (received from detection or from external    sources).

Integratory processing unit 103 may make those changes when the LIDARsensing unit is installed, from time to time, based on detection data,based on timing of incoming requests for data, and so on.

FIG. 10A illustrates distributed LIDAR system 900 in which integratoryprocessing unit 103 modified the detection ranges of otherwise identicalLIDAR sensing units, in accordance with examples of the presentlydisclosed subject matter.

FIG. 10B illustrates the maximal FOV 710 of an anchored LIDAR sensingunit 101 (e.g., a LIDAR system 100) in different operational states, inaccordance with examples of the presently disclosed subject matter. Indiagram A, the entire FOV is inspected with equally spaced identicalpulses 720. In diagram B, the scanning pattern 730 is modified to coveronly part of the FOV, and the resolution of pulses 720 is modified inpart of the FOV. In diagram C, the number of pulses issued at part ofthe FOV is reduced (e.g., for saving power in a less interesting area ofthe FOV). In diagram D, the scanning pattern 730 is modified to cover aregion of interest, but the spatial frequency of pulses 720 is notmodified. It will be clear to a person who is of skill in the art thatthese are just some of the options by which integratory processing unit103 may change the scanning of an anchored LIDAR sensing unit 101.

It is noted that the modification may be made in different ways, such asparameters (e.g., pulse timing, scanning pattern of a mirror),mechanical changes (e.g., position of optical components within thesystem, rotating of the entire LIDAR unit), and in other forms.

V2V, V2X LIDAR systems

According to a disclosed embodiment, a vehicle on which one or moreLIDAR detection systems are deployed (whether system 100 or any othertype of LIDAR detection systems) may include at least one communicationunit which is configured to wirelessly transmit to external systems(e.g., other vehicles, regional processing units 103, servers, etc.)LIDAR detection information (whether raw or processed) such as any oneor more of the following:

-   viii. A point cloud;-   ix. A 3D model;-   x. Detection to other objects in the scene;-   xi. Velocity of objects in the scene;-   xii. Classification of objects in the scene.

The communication with the external units may be managed by the host,but this is not necessarily so. A receiving vehicle may be combined itsown LIDAR detection information (e.g., point cloud, geolocatedclassified objects) with the LIDAR detection information received fromanother vehicle to have a more complete model of its surrounding.

Sensor-Carrying Scouting Vehicle

FIGS. 11A and 11B illustrate examples of a sensor-carrying scoutingvehicle 810, in accordance with examples of the presently disclosedsubject matter. Scouting vehicle 810 may include one or more sensors 820such as: LIDARs, cameras, RADARs, ultrasonic sensors, and so on.Scouting vehicle 810 may move ahead of another vehicle 830 or group ofvehicles 830 (e.g., train, truck, a platoon of cars/trucks), andtransmit to the other one or more vehicles 830 information regarding thescene into which that other one or more vehicles are headed. Forexample, the braking distance of a loaded train or truck may be longerthan the detection range of a LIDAR, in which case one or more scoutingvehicles may be used in order to provide sufficient scene information tothe train, truck, etc. The information collected by the one or morescouting vehicles 810 may be combined with information from therecipient vehicle 830 itself and/or from an external LIDAR system(whether distributed or not), but this is not necessarily so. Themovement of scouting vehicle 810 may be controlled by the recipientvehicle 830, but this is not necessarily so. The movement of scoutingvehicle 810 may be controlled based on detection data of its one or moresensors 820, but this is not necessarily so. The movement of scoutingvehicle 810 may be controlled by information provided by the recipientvehicle 830, but this is not necessarily so. Scouting vehicle 810 mayalso be an aerial scouting vehicle such as a drone, which may and maynot be connected to the recipient vehicle or to anther scouting vehicle(e.g., by wire).

The foregoing description has been presented for purposes ofillustration. It is not exhaustive and is not limited to the preciseforms or embodiments disclosed. Modifications and adaptations will beapparent to those skilled in the art from consideration of thespecification and practice of the disclosed embodiments. Additionally,although aspects of the disclosed embodiments are described as beingstored in memory, one skilled in the art will appreciate that theseaspects can also be stored on other types of computer readable media,such as secondary storage devices, for example, hard disks or CD ROM, orother forms of RAM or ROM, USB media, DVD, Blu-ray™, or other opticaldrive media.

Methods corresponding to the capabilities of any of the systems andcomponents discussed above are considered part of the disclosedembodiments, and are not described in full for reasons of brevity.Computer programs based on the written description and disclosed methodsare within the skill of an experienced developer. The various programsor program modules can be created using any of the techniques known toone skilled in the art or can be designed in connection with existingsoftware. For example, program sections or program modules can bedesigned in or by means of .Net Framework, .Net Compact Framework (andrelated languages, such as Visual Basic, C, etc.), Java, C++,Objective-C, HTML, HTML/AJAX combinations, XML, or HTML with includedJava applets.

Moreover, while illustrative embodiments have been described herein, thescope of any and all embodiments having equivalent elements,modifications, omissions, combinations (e.g., of aspects across variousembodiments), adaptations and/or alterations as would be appreciated bythose skilled in the art based on the present disclosure. Thelimitations in the claims are to be interpreted broadly based on thelanguage employed in the claims and not limited to examples described inthe present specification or during the prosecution of the application.The examples are to be construed as non-exclusive. Furthermore, thesteps of the disclosed methods may be modified in any manner, includingby reordering steps and/or inserting or deleting steps. It is intended,therefore, that the specification and examples be considered asillustrative only, with a true scope and spirit being indicated by thefollowing claims and their full scope of equivalents.

What is claimed is:
 1. A LIDAR system, the LIDAR system comprising: aplurality of anchored LIDAR sensing units, each anchored LIDAR sensingunit comprising at least: a housing; at least one detector, mounted inthe housing, configured to detect light signals arriving from objects ina field of view of the anchored LIDAR sensing unit; a communicationunit, configured to output detection information which is based onoutputs of the at least one detector and which is indicative ofexistence of the objects ; and at least one integratory processing unit,configured to receive the detection information from two or more of theplurality of anchored LIDAR sensing units, to process the receiveddetection information to provide a three dimensional (3D) model of ascene which is larger than any of the field of views of the independentanchored LIDAR sensing units, wherein the at least one integratoryprocessing unit is configured to: wirelessly transmit to a firstvehicle, based on at least one of a type, a speed, or a location of thefirst vehicle, first 3D data pertaining to a spatial area at a firsttime; and wireles sly transmit to a second vehicle, based on at leastone of a type, a speed, or a location of the second vehicle, second 3Ddata pertaining to the spatial area at the first time, wherein the first3D data and the second 3D data comprise 3D data indicative of portionsof the 3D model in different levels of details.
 2. The LIDAR system ofclaim 1, wherein two or more of the plurality of anchored LIDAR sensingunits are mounted at a height of at least 3 meters above ground level.3. The LIDAR system of claim 1, wherein at least one of the plurality ofanchored LIDAR sensing units further comprises a processor, configuredto process the light signals to determine existence of objects in thefield of view of the LIDAR sensing unit.
 4. The LIDAR system of claim 1,wherein integratory processing unit is an anchored to a stationaryobject.
 5. The LIDAR system of claim 1, wherein at least one of theplurality of anchored LIDAR sensing units further include at least oneadditional sensor selected from a group consisting of: a camera, aRADAR, and an ultrasound detector.
 6. The LIDAR system of claim 4,comprising at least one processor configured to determine operationalparameters for at least one of the plurality of anchored LIDAR sensingunits based on detection information of the at least one additionalsensor.
 7. The LIDAR system of claim 1, wherein the at least oneintegratory processing unit is configured to further receive detectioninformation from at least one additional anchored sensor selected from agroup consisting of: a camera, a RADAR, and an ultrasound detector; toprocess detection information of the at least one additional anchoredsensor together with the received detection information to provide athree dimensional (3D) model of a scene which is larger than any of thefield of views of the independent anchored LIDAR sensing units.
 8. TheLIDAR system of claim 6, comprising at least one processor configured todetermine operational parameters for at least one of the plurality ofanchored LIDAR sensing units based on detection information of the atleast one additional sensor.
 9. The LIDAR system of claim 1, wherein adistance between a first anchored LIDAR sensing unit of the plurality ofanchored LIDAR sensing units and a second anchored LIDAR sensing unit ofthe plurality of anchored LIDAR sensing units exceeds a first detectionrange of the first anchored LIDAR sensing unit and a second detectionrange of the second anchored LIDAR sensing unit.
 10. The LIDAR system ofclaim 1, wherein a distance between a first anchored LIDAR sensing unitof the plurality of anchored LIDAR sensing units and at least oneintegratory processing unit exceeds a first detection range of the firstanchored LIDAR sensing unit.
 11. The LIDAR system of claim 1, whereinthe at least one integratory processing unit is configured to: receivefrom multiple anchored LIDAR sensing units of the plurality of anchoredLIDAR sensing units detection information pertaining to a common spatialarea comprised in the fields of view of the multiple anchored LIDARsensing unit; process the received detection information to provide a 3Dmodel of the common spatial area which comprises 3D information ofopposing sides of an object in the common spatial area, wherein none ofthe multiple anchored LIDAR sensing units detects all of the opposingsides.
 12. The LIDAR system of claim 1, comprising a synchronizationcontroller which is configured to instruct a first anchored LIDARsensing unit of the plurality of anchored LIDAR sensing units to modifyits light emission scheme so as to prevent interferences by the firstanchored LIDAR sensing unit to a second anchored LIDAR sensing unit ofthe plurality of anchored LIDAR.
 13. The LIDAR system of claim 1,wherein the at least one integratory processing unit is configured toinstruct a driving decision of a vehicle in the scene based on the 3Dmodel.
 14. A method for LIDAR processing in a distributed LIDAR system,the method comprising: receiving detection information from a pluralityof anchored LIDAR sensing units, each covering a different field ofview; processing the received detection information to provide a 3Dmodel of a scene which is larger than any of the field of views of theindependent anchored LIDAR sensing units; wireles sly transmitting to afirst vehicle, based on at least one of a type, a speed, or a locationof the first vehicle, first 3D data pertaining to a spatial area at afirst time; and wirelessly transmitting, to a second vehicle, based onat least one of a type, a speed, or a location of the second vehicle,second 3D data pertaining to the spatial area at the first time, whereinthe first 3D data and the second 3D data comprise 3D data indicative ofportions of the 3D model in different levels of details.
 15. Anintegratory LIDAR system, the integratory LIDAR system comprising: acommunication module for receiving detection information from aplurality of anchored LIDAR sensing units; and at least one integratoryprocessing unit configured to process the detection information receivedfrom the plurality of anchored LIDAR sensing unit to provide a 3D modelof a scene which is larger than any of the field of views of theindependent anchored LIDAR sensing units, wherein the at least oneintegratory processing unit is further configured to: wirelesslytransmit to a first vehicle, based on at least one of a type, a speed,or a location of the first vehicle, first 3D data pertaining to aspatial area at a first time; and wireles sly transmit to a secondvehicle, based on at least one of a type, a speed, or a location of thesecond vehicle, second 3D data pertaining to the spatial area at thefirst time, wherein the first 3D data and the second 3D data comprise 3Ddata indicative of portions of the 3D model in different levels ofdetails, wherein the at least one integratory processing unit isconfigured to: wirelessly transmit to a first vehicle, based on at leastone of a type, a speed, or a location of the first vehicle, first 3Ddata pertaining to a spatial area at a first time; and wireles slytransmit to a second vehicle, based on at least one of a type, a speed,or a location of the second vehicle, second 3D data pertaining to thespatial area at the first time, wherein the first 3D data and the second3D data comprise 3D data indicative of portions of the 3D model indifferent levels of details.